HK1248945B - Methods and apparatus to perform audio sensor selection in an audience measurement device - Google Patents

Description

Method and apparatus for performing audio sensor selection in an audience measurement device

Technical Field

The present disclosure relates generally to media monitoring and, more particularly, to methods and apparatus for performing audio sensor selection in an audience measurement device.

Background Art

Monitoring companies desire knowledge about how users interact with media devices (such as smartphones, tablets, laptops, smart TVs, etc.). To facilitate this monitoring, monitoring companies recruit panelists and install meters at those panelists' media presentation locations. The meters monitor the media presentations and send media monitoring information to the monitoring company's central facilities. This media monitoring information enables the media monitoring company to monitor exposure to advertisements, determine advertising effectiveness, determine user behavior, identify purchasing behavior associated with various demographics, and more.

Summary of the Invention

According to one aspect of the present invention, a method for performing audio sensor selection in an audience metering device is provided, the method comprising the following steps: identifying a plurality of audio sensor configurations supported by the audience metering device; calculating, by executing instructions with a processor, a first quality metric of a first media identifier determined from first audio received via a first audio sensor configuration among the audio sensor configurations; calculating, by executing instructions with the processor, a second quality metric of a second media identifier determined from second audio received via a second audio sensor configuration among the audio sensor configurations; selecting, based on a comparison of the first quality metric and the second quality metric, one of the first audio sensor configuration among the audio sensor configurations or the second audio sensor configuration among the audio sensor configurations; and performing media monitoring at the audience metering device using the selected one of the audio sensor configurations.

According to another aspect of the present invention, an apparatus for performing audio sensor selection is provided, the apparatus comprising: at least two audio sensors for receiving audio at an audience metering device; a selection tester for identifying a plurality of audio sensor configurations supported by the at least two audio sensors of the audience metering device, obtaining a first quality metric of a first media identifier corresponding to audio received via a first audio sensor configuration of the audio sensor configurations, obtaining a second quality metric of a second media identifier corresponding to audio received via a second audio sensor configuration of the audio sensor configurations; and selecting one of the first audio sensor configuration of the audio sensor configurations or the second audio sensor configuration of the audio sensor configurations based on a comparison of the first quality metric and the second quality metric; and a media identifier for identifying the audio received at the audience metering device using the selected one of the audio sensor configurations.

According to another aspect of the present invention, a non-transitory computer-readable medium comprising instructions is provided that, when executed, causes an audience metering device to at least: identify a plurality of audio sensor configurations supported by the audience metering device; calculate a first quality metric of a first media identifier determined from first audio received via a first audio sensor configuration of the audio sensor configurations; calculate a second quality metric of a second media identifier determined from second audio received via a second audio sensor configuration of the audio sensor configurations; select one of the first audio sensor configuration of the audio sensor configurations or the second audio sensor configuration of the audio sensor configurations based on a comparison of the first quality metric and the second quality metric; and perform media monitoring at the audience metering device using the selected one of the audio sensor configurations.

According to another aspect of the present invention, an apparatus for performing audio sensor selection is provided, the apparatus comprising: at least two audio sensing devices for receiving audio at an audience metering device; a selection test device for identifying a plurality of audio sensor configurations supported by the at least two audio sensors of the audience metering device; obtaining a first quality metric of a first media identifier corresponding to audio received via a first audio sensor configuration of the audio sensor configurations; obtaining a second quality metric of a second media identifier corresponding to audio received via a second audio sensor configuration of the audio sensor configurations; and selecting one of the first audio sensor configuration of the audio sensor configurations or the second audio sensor configuration of the audio sensor configurations based on a comparison of the first quality metric and the second quality metric; and a media identification device for identifying the audio received at the audience metering device using the selected one of the audio sensor configurations.

BRIEF DESCRIPTION OF THE DRAWINGS

1 is a block diagram of an example system constructed in accordance with the teachings of the present disclosure for performing audio sensor selection in an audience measurement device.

FIG. 2 is a block diagram of the example meter of FIG. 1 .

3 is an example front view of the example meter of FIG. 1 and/or FIG. 2 .

4 is an example rear view of the example instrument of FIG. 1 and/or FIG. 2 .

5 is an example top view of the example meter of FIG. 1 and/or FIG. 2 .

6 is a diagram showing an example configuration of the media presentation environment of FIG. 1 , in which rear-facing speakers are used.

7 is a diagram showing an example configuration of the media presentation environment of FIG. 1 , in which front-facing speakers are used.

8 is a diagram showing an example configuration of the media presentation environment of FIG. 1 , in which a surround sound speaker system is used.

9 is a flow diagram representative of example machine readable instructions that may be executed to implement the meter of FIG. 1 and/or FIG. 2 to perform media recognition utilizing a selected audio sensor configuration.

10 is a flow diagram representative of example machine readable instructions that may be executed to implement the example meter of FIG. 1 and/or FIG. 2 to send media monitoring information to the example central facility of FIG. 1 .

11 is a flow diagram representative of example machine readable instructions that may be executed to implement the example meter of FIG. 1 and/or FIG. 2 to update a selected audio sensor configuration using input from a configuration interface.

12 is a flow diagram representative of example machine readable instructions that may be executed to implement the example meter of FIG. 1 and/or FIG. 2 to update a selected audio sensor configuration based on automatic testing of different audio sensor configurations.

13 is an example data table showing signal-to-noise ratios of identified watermarks determined in relation to different audio sensor configurations.

14 is a block diagram of an example processor platform capable of executing the machine-readable instructions of FIG. 9 , FIG. 10 , FIG. 11 , and/or FIG. 12 to perform audio sensor selection in accordance with the teachings of the present disclosure.

The drawings are not drawn to scale. Wherever possible, the same reference numbers will be used throughout the drawings and accompanying written description to refer to the same or like parts.

DETAILED DESCRIPTION

Traditionally, audience measurement entities (also referred to herein as "rating entities" or "monitoring companies") determine the demographic reach of advertising and media programming based on registered panelists. That is, the audience measurement entity enrolls individuals who have consented to be monitored into a panel. During enrollment, the audience measurement entity receives demographic information from the enrolled individuals, allowing subsequent correlations to be drawn between those panelists' advertising/media exposure and different demographic markets.

FIG1 is an illustration of an example audience measurement system constructed in accordance with the teachings of the present disclosure for performing symbol-based watermark detection. In the illustrated example of FIG1 , an example media presentation environment 102 includes example panelists 104, 106, an example media presentation device 110 that receives media from an example media source 112, and an example meter 114. The meter 114 identifies the media presented by the media presentation device 110 and reports media monitoring information to an example central facility 190 of an example audience measurement entity via an example gateway 140 and an example network 180.

In the illustrated example of FIG1 , the example media presentation environment 102 is a room in a household (e.g., a room in a panelist's home, such as the home of a "Nielsen family"). In the illustrated example of FIG1 , the example panelists 104, 106 of the household have been statistically selected to obtain demographic and/or demographic media ratings data (e.g., television ratings data). People become panelists via, for example, a user interface presented on a media device (e.g., via the media presentation device 110, via a website, etc.). People become panelists in additional or alternative ways, such as, for example, via telephone interviews, completing online surveys, etc. Additionally or alternatively, people may be contacted and/or recruited using any desired methodology (e.g., random selection, statistical selection, telephone solicitation, internet advertising, surveys, advertising in shopping malls, product packaging, etc.). In some examples, an entire family may be recruited as panelists for a household. That is, while a mother, father, son, and daughter may each be identified as individual panelists, their viewing activity generally occurs within the household.

1 , one or more panelists 104, 106 of a household have registered with an audience measurement entity (e.g., agreed to become panelists) and have provided their demographic information to the audience measurement entity as part of the registration process to enable the demographic information to be associated with media exposure activity (e.g., television exposure, radio exposure, internet exposure, etc.). The demographic data includes, for example, the panelist's age, gender, income level, education level, marital status, geographic location, ethnicity, etc. Although the example media presentation environment 102 is a household in the example of FIG1 , the example media presentation environment 102 may additionally or alternatively be any other type of environment, such as, for example, a movie theater, a restaurant, a hotel, a retail store, an arena, etc.

In the illustrated example of Fig. 1, example media presentation device 110 is a television set. However, example media presentation device 110 may correspond to any type of audio, video and/or multimedia presentation device that can present media audibly and/or visually. In the illustrated example of Fig. 1, media presentation device 110 communicates with example audio/video receiver 118. In some examples, media presentation device 110 (e.g., television set) can transmit audio to another media presentation device (e.g., audio/video receiver 118) to output through one or more speakers (e.g., surround sound speakers, sound bars, etc.). As another example, media presentation device 110 may correspond to a multimedia computer system, a personal digital assistant, a cellular/mobile smart phone, a radio, a home theater system, the audio of storage and/or the video (such as a digital video recorder or a digital versatile disk) replayed from memory, a web page and/or any other communication device that can present media to an audience (e.g., panelists 104, 106).

The media presentation device 110 receives media from a media source 112. The media source 112 can be any type of media provider, such as, but not limited to, a cable television media service provider, a radio frequency (RF) media provider, an Internet-based provider (e.g., IPTV), a satellite media service provider, etc., and/or any combination thereof. The media can be radio media, television media, pay-per-view media, movies, Internet Protocol television (IPTV), satellite television (TV), Internet radio, satellite radio, digital television, digital radio, stored media (e.g., compact disc (CD), digital versatile disc (DVD), Blu-ray disc, etc.), any other type of broadcast, multicast, and/or unicast media, audio and/or video media presented (e.g., streamed) via the Internet, video games, targeted broadcasts, satellite broadcasts, video on demand, etc. For example, the media presentation device 110 may correspond to a television and/or display device that supports the National Television Standards Committee (NTSC) standard, the Phase Alternation Line (PAL) standard, the Système pour Couleur avec Mémoire (SECAM) standard, standards developed by the Advanced Television Systems Committee (ATSC), such as High Definition Television (HDTV), standards developed by the Digital Video Broadcasting (DVB) initiative, etc. Advertisements, such as advertisements and/or previews of other broadcast programs provided or to be provided by the media source 112 or the like, are also typically included in the media.

In the examples disclosed herein, an audience measurement entity provides a meter 114 to panelists 104, 106 (or panelist households) such that the meter 114 can be installed by the panelists 104, 106 by simply powering the meter 114 and placing the meter 114 in the media presentation environment 102 and/or near the media presentation device 110 (e.g., near a television). In some examples, the meter 114 can be provided to the panelists 104, 106 by an entity other than the audience measurement entity. In some examples, more complex installation activities can be performed, such as attaching the meter 114 to the media presentation device 110, electronically connecting the meter 114 to the media presentation device 110, etc. The example meter 114 detects exposure to media and electronically stores monitoring information for the presented media (e.g., a code detected with the presented media, a signature of the presented media, an identifier of the panelist present at the time of presentation, a timestamp of the presentation time). The stored monitoring information is then sent back to the central facility 190 via the gateway 140 and the network 180. Although the media monitoring information is sent via electronic transmission in the illustrated example of FIG. 1 , the media monitoring information may additionally or alternatively be delivered in any other manner, such as, for example, by physically mailing the meter 114 , by physically mailing a memory of the meter 114 , etc.

The illustrated example meter 114 combines audience measurement data and people metering data. For example, the audience measurement data is determined by monitoring the media output by the media presentation device 110 and/or other media presentation devices, and the audience identification data (also referred to as demographic data, people monitoring data, etc.) is determined from the people monitoring data provided to the meter 114. Thus, the example meter 114 provides the dual functionality of an audience measurement meter that collects audience measurement data and a viewership meter that collects and/or correlates demographic information corresponding to the collected audience measurement data.

For example, the illustrated example meter 114 collects media identification information and/or data (e.g., signatures, fingerprints, codes, tuned channel identification information, exposure time information, etc.) and personnel data (e.g., user identifiers, demographic data associated with audience members, etc.). The media identification information and personnel data can be combined to generate, for example, media exposure data (e.g., ratings data) that indicates the number and/or type of people who were exposed to specific media distributed via the media presentation device 110. To extract the media identification data, the illustrated example meter 114 of FIG. 1 monitors watermarks (sometimes referred to as codes) included in the presented data.

In the examples disclosed herein, to monitor media presented by media presentation device 110, an example meter 114 senses audio (e.g., acoustic signals or ambient audio) output (e.g., emitted) by media presentation device 110 and/or some other audio presentation system (e.g., audio/video receiver 118 of FIG. 1 ). For example, meter 114 processes signals obtained from media presentation device 110 to detect media and/or source identification signals (e.g., audio watermarks) embedded in portions (e.g., audio portions) of the media presented by media presentation device 110. To, for example, sense ambient audio output by media presentation device 110, example meter 114 includes a plurality of example audio sensors (e.g., microphones and/or other acoustic sensors). In some examples, meter 114 can process audio signals obtained from media presentation device 110 via a direct cable connection to detect media and/or source identification audio watermarks embedded in these audio signals.

In some examples, media presentation device 110 utilizes rear-facing speakers. When rear-facing speakers are used, utilizing a forward-facing audio sensor in meter 114 to receive the audio output by the rear-facing speakers generally does not facilitate good watermark identification. In contrast, utilizing the rear-facing audio sensor of meter 114 in the presence of rear-facing speakers may result in better identification of watermarks included in the audio output by the media presentation device. In the examples disclosed herein, the audio sensor of meter 114 is selected to facilitate the best possible watermark identification. For example, when the media presentation device utilizes rear-facing speakers, the rear-facing audio sensor of meter 114 may be utilized; when the media presentation device utilizes front-facing speakers, the front-facing audio sensor of meter 114 may be utilized. Moreover, different configurations of the audio sensors of the meter 114 can be used, for example, to account for different acoustic environments that produce different levels of recognition of watermarks, to account for differently configured audio systems (e.g., a soundbar system, a 5.1 surround sound system, a 7.1 surround sound system, etc.), with different configurations being used based on the selected input to the media presentation device 110 (e.g., surround sound speakers can be used when presenting movies, while rear-facing speakers can be used when presenting broadcast television, etc.).

In some examples, meter 114 can be physically coupled to media presentation device 110 and configured to capture audio externally emitted by media presentation device 110 (e.g., free-field audio), eliminating the need for a direct physical connection to the audio output of media presentation device 110. For example, the illustrated example meter 114 can employ non-intrusive monitoring that does not involve any physical connection to media presentation device 110 (e.g., via a connection, a connection, an acoustic watermark, etc.) and/or intrusive monitoring that involves one or more physical connections to the media presentation device (e.g., via a USB connection, a High Definition Media Interface (HDMI) connection, an Ethernet cable connection, etc.). In some examples, intrusive monitoring can be used to facilitate determining which audio sensor(s) meter 114 should use. For example, meter 114 can be connected to the media presentation device using a universal serial bus (USB) cable, allowing meter 114 to identify the speaker configuration of media presentation device 110. Based on this information, meter 114 can select an appropriate audio sensor best suited for monitoring the audio output by media presentation device 110. For example, if the media presentation device 110 indicates that front-facing speakers are being used, the meter 114 may select a front-facing audio sensor for monitoring the outputted audio.

To generate media exposure data, identification of the media to which the audience was exposed is correlated with personnel data (e.g., presence information) collected by meter 114. The illustrated example meter 114 collects input (e.g., audience identification data) representing the identities of audience members (e.g., panelists 104, 106). In some examples, meter 114 collects audience identification data by periodically or aperiodically prompting audience members in media presentation environment 102 to identify themselves as present in the audience. In some examples, meter 114 prompts audience members to self-identify in response to predetermined events (e.g., when media presentation device 110 is turned on, the channel is changed, an infrared control signal is detected, etc.). The audience identification data and exposure data can then be compiled with demographic data collected from audience members, such as panelists 104, 106, during registration to obtain metrics reflecting, for example, the demographic composition of the audience. Demographic data includes, for example, the panelists' age, gender, income level, education level, marital status, geographic location, ethnicity, etc.

In some examples, meter 114 can be configured to receive panelist information via an input device, such as, for example, a remote control, a cellular phone, or the like. In these examples, meter 114 prompts audience members to indicate their presence by pressing an appropriate input key on the input device. The illustrated example meter 114 can also determine when to prompt audience members to enter information into meter 114. In some examples, meter 114 of FIG. 1 supports audio watermarking for presence monitoring, which enables meter 114 to detect the presence of a panelist identification meter near media presentation device 110 (e.g., within media presentation environment 102). For example, an audio sensor of meter 114 can be capable of sensing example audio output (e.g., emitted) by an example panelist identification meter, such as, for example, a wristband, a cellular phone, or the like, uniquely associated with a particular panelist. The audio output by the example panelist identification meter can include, for example, one or more audio watermarks to facilitate identification of the panelist identification meter and/or the panelist 104 associated with the panelist identification meter.

The example meter 114 of the illustrated example communicates with a remotely located central facility 190 of an audience measurement entity. In the illustrated example of FIG1 , the example meter 114 communicates with the central facility 190 via a gateway 140 and a network 180. The example metering device 114 of FIG1 sends media identification data and/or audience identification data to the central facility 190 periodically, aperiodically, and/or upon request of the central facility 190.

The example gateway 140 of the illustrated example of FIG. 1 is a router that enables the meter 114 and/or other devices in the media presentation environment (eg, the media presentation device 110 ) to communicate with the network 180 (eg, the Internet).

In some examples, the example gateway 140 facilitates the transfer of media from the media source 112 to the media presentation device 110 via the Internet. In some examples, the example gateway 140 includes gateway functionality such as modem capabilities. In some other examples, the example gateway 140 is implemented in two or more devices (e.g., a router, a modem, a switch, a firewall, etc.). The example gateway 140 can communicate with the network 126 via Ethernet, a digital subscriber line (DSL), a telephone line, a coaxial cable, a USB connection, a Bluetooth connection, any wireless connection, etc.

In some examples, the example gateway 140 hosts a local area network (LAN) for the media presentation environment 102. In this illustrated example, the LAN is a wireless local area network (WLAN) and allows the meter 114, the media presentation device 110, etc. to send and/or receive data via the Internet. Alternatively, the gateway 140 can be connected to such a LAN. In some examples, the example gateway 140 is implemented by a cellular communication system and can, for example, enable the meter 114 to send information to the central facility 190 using a cellular connection.

The illustrated example network 180 is a wide area network (WAN) such as the Internet. However, in some examples, a local network may additionally or alternatively be used. Furthermore, the example network 180 may be implemented using any type of public or private network such as, but not limited to, the Internet, a telephone network, a local area network ("LAN"), a cable television network, and/or a wireless network, or any combination thereof.

The illustrated central facility 190 is implemented by one or more servers. The central facility 190 processes and stores data received from the meters 114. For example, the example central facility 190 of FIG1 combines viewer identification data and program identification data from multiple households to generate aggregated media monitoring information. The central facility 190 generates reports for advertisers, program producers, and/or other interested parties based on the compiled demographic data. These reports include inferences about the size and demographic composition of the audience for content, channels, and/or advertisements based on the demographics and behavior of the monitored panelists.

As noted above, the meter 114 of the illustrated example provides a combination of media metering and people metering. The meter 114 of FIG. 1 includes its own housing, processor, memory, and/or software for performing the desired media monitoring and/or people monitoring functions. The example meter 114 of FIG. 1 is a fixed device disposed on or near the media presentation device 110. In order to identify and/or confirm the presence of panelists present in the media presentation environment 102, the example meter 114 of the illustrated example includes a display. For example, the display provides identification of the panelists 104, 106 present in the media presentation environment 102. For example, in the illustrated example, the meter 114 displays indicia (e.g., illuminated numerical labels 1, 2, 3, etc.) that identify and/or confirm the presence of the first panelist 104, the second panelist 106, etc. In the illustrated example, the meter 114 is attached to the top of the media presentation device 110. However, the meter 114 may be attached to the media presentation device in any other orientation, such as, for example, on the side of the media presentation device 110, on the bottom of the media presentation device 110, and/or may not be attached to the media presentation device 110. For example, the meter 114 may be placed at a location where the media presentation device 110 is attached.

Figure 2 is a block diagram illustrating an example implementation of the example meter 114 of Figure 1. The example meter 114 of Figure 2 includes example audio sensors 202, 204, 206, 208, an example audio sensor selector 210, an example configuration memory 220, an example media identifier 230, an example selection tester 240, an example configuration interface 245, an example audience measurement data controller 250, an example data storage 255, an example network communicator 260, an example person identifier 270, an example power receiver 280, and an example battery 285.

The example audio sensors 202, 204, 206, 208 of the illustrated example of FIG2 are implemented by microphones and/or other acoustic sensors. The example audio sensors 202, 204, 206, 208 each receive ambient sound (e.g., free-field audio) including audible media presented near the meter 114. Alternatively, one or more of the audio sensors 202, 204, 206, 208 can be implemented via a line-in connection. The line-in connection can allow one or more external microphones to be used with the meter 114, and/or in some examples, can enable one or more of the audio sensors 202, 204, 206, 208 to be directly connected to an output of a media presentation device (e.g., an auxiliary output of a television, an auxiliary output of an audio/video receiver of a home entertainment system, etc.). Advantageously, the meter 114 is positioned so that the audio sensors 202, 204, 206, 208 receive the ambient audio produced by the television and/or other devices of the home entertainment system at a quality sufficient to recognize the media presented by the media presentation device 110 and/or other devices (e.g., the audio/video receiver 118) of the media presentation environment 102. For example, in the examples disclosed herein, the meter 114 may be placed on top of the television, secured to the bottom of the television, etc.

In the example of FIG2 , four audio sensors 202, 204, 206, and 208 are shown. Each of the four audio sensors 202, 204, 206, and 208 corresponds to a front right microphone, a front left microphone, a rear right microphone, and a rear left microphone, respectively. Although four audio sensors are used in the example of FIG2 , any number of audio sensors may additionally or alternatively be used. In the examples of FIG3 , FIG4 , and/or FIG5 below, example arrangements of example audio sensors 202, 204, 206, and 208 on meter 114 are shown.

2 combines the audio received by the audio sensors 202, 204, 206, 208 to prepare a combined audio signal for analysis by the media identifier 230. In some examples, the example audio sensor selector 210 combines the audio received by the audio sensors 202, 204, 206, 208 by mixing the audio. In the examples disclosed herein, the example audio sensor selector 210 consults the example configuration memory 220 to identify which audio sensors 202, 204, 206, 208 should pass their respective received audio signals to the media identifier 230. Conversely, in some examples, the example audio sensor selector 210 can identify which audio sensors 202, 204, 206, 208 should not pass (e.g., should be blocked) and block those audio sensors 202, 204, 206, 208 accordingly.

In the illustrated example of FIG. 2 , the example audio sensor selector 210 adds the audio waveforms received via each of the selected audio sensors 202 , 204 , 206 , and 208 . However, in some examples, additional processing may be performed, such as, for example, applying corresponding gains to one or more of the selected audio sensors 202 , 204 , 206 , and 208 . For example, the audio signal received via the first audio sensor 202 may be amplified by a factor of two and combined with the audio signal received via the second audio sensor 204 to create a combined audio signal for analysis by the media identifier 230 . In the examples disclosed herein, the audio waveforms received via each of the selected audio sensors 202 , 204 , 206 , and 208 are combined in the time domain. However, the audio waveforms may be combined in any other manner. For example, the example audio waveforms may be combined in the frequency domain. Furthermore, in the examples disclosed herein, the example audio waveforms are combined before digitization. However, in some examples, the example audio waveforms may be combined after digitization.

The example configuration memory 220 of the illustrated example of FIG2 stores an audio sensor configuration that identifies which of the audio sensors 202, 204, 206, 208 should be selected by the audio sensor selector 210 to form the audio signal to be processed by the media identifier 230. However, any other additional configuration and/or operational information may additionally or alternatively be stored. For example, WiFi credentials to be used by the network communicator 260, group member and/or family identifiers, etc. may be stored in the configuration memory 220. The example configuration memory 220 may be updated by, for example, the configuration interface 245 and/or the selection tester 240. The example configuration memory 220 of the illustrated example of FIG2 may be implemented by any device for storing data, such as, for example, flash memory, magnetic media, optical media, etc. Furthermore, the data stored in the example configuration memory 220 may have any data format, such as, for example, binary data, comma-delimited data, tab-delimited data, Structured Query Language (SQL) structures, etc.

The example media identifier 230 of the illustrated example of FIG2 analyzes audio received via one or more of the audio sensors 202, 204, 206, and 208 and identifies the media being presented. The example media identifier 230 of the illustrated example outputs an identifier of the media (e.g., media identification information) to the audience measurement data controller 250. In the illustrated example of FIG2, the example media identifier 230 outputs a quality metric for the media identifier. As used herein, a quality metric is defined as any value representing the strength and/or quality of a detected watermark/code. In the examples disclosed herein, the quality metric is a signal-to-noise ratio. However, any other quality metric may additionally or alternatively be used, such as, for example, a score, a bit error rate (BER), a volume level, etc. Moreover, in some examples, different values representing the strength and/or quality of a detected watermark/code may be combined to form a quality metric. For example, the signal-to-noise ratio may be combined with the BER to form a quality metric.

In the examples disclosed herein, media identifier 230 utilizes audio watermarking technology to identify media. Audio watermarking is a technique used to identify media such as television broadcasts, radio broadcasts, advertisements (television and/or radio), downloaded media, streaming media, pre-packaged media, and the like. Existing audio watermarking technology identifies media by embedding one or more audio codes (e.g., one or more watermarks) (such as media identification information and/or one or more identifiers that can be mapped to media identification information) into the audio and/or video components of the media. In some examples, the audio and/or video components of the media are selected to have signal characteristics sufficient to conceal the watermark. As used herein, the terms "code" and/or "watermark" are used interchangeably and are defined to mean any identifying information (e.g., an identifier) that can be inserted or embedded into the audio or video of media (e.g., a program or advertisement) for the purpose of identifying the media or for another purpose such as tuning (e.g., a packet identification header). As used herein, "media" refers to audio and/or visual (still or motion) content and/or advertisements. In some examples, to identify watermarked media, the watermark is extracted and used to access a table of reference watermarks that are mapped to media identification information.

In some examples, media identifier 230 may utilize signature-based media identification techniques. Unlike media monitoring techniques based on codes and/or watermarks included with and/or embedded in the monitored media, fingerprint- or signature-based media monitoring techniques typically use one or more inherent characteristics of the monitored media to generate a substantially unique proxy for the media during a monitoring interval. This representation is referred to as a signature or fingerprint and can take any form (e.g., a series of digital values, a waveform, etc.) that represents any aspect of a media signal (e.g., the audio and/or video signals forming the media presentation being monitored). A signature can be a series of signatures collected continuously during a time interval. A good signature may be repeated when processing the same media presentation, but is unique relative to other (e.g., different) presentations of other (e.g., different) media. Therefore, the terms "fingerprint" and "signature" are used interchangeably herein and are defined herein to mean a proxy for identifying media generated from one or more inherent characteristics of the media.

Signature-based media monitoring generally involves determining (e.g., generating and/or collecting) a signature representing a media signal (e.g., an audio signal and/or a video signal) output by a monitored media device and comparing the monitored signature to one or more reference signatures corresponding to known (e.g., reference) media sources. Various comparison criteria (such as cross-correlation values, Hamming distances, etc.) can be evaluated to determine whether the monitored signature matches a particular reference signature. When a match is found between the monitored signature and one of the reference signatures, the monitored media can be identified as corresponding to the particular reference media represented by the reference signature that matches the monitored signature. Because attributes (such as identifiers of the media, presentation time, broadcast channel, etc.) are collected for the reference signatures, these attributes can then be associated with the monitored media whose monitored signature matches the reference signature. Example systems for identifying media based on codes and/or signatures are already known and were first disclosed in U.S. Pat. No. 5,481,294 to Thomas, which is incorporated herein by reference in its entirety.

The example selection tester 240 of the illustrated example of FIG2 identifies possible configurations of audio sensors that may be used to receive audio. The example selection tester 240 instructs the example audio sensor selector 210 to iterate through each of the different possible configurations of the audio sensor and monitor the output of the media identifier 230 indicating the signal-to-noise ratio of the detected media identification information (e.g., watermark) for the corresponding configuration. The example selection tester 240 then selects the configuration of the audio sensor with the desired or best (e.g., largest) signal-to-noise ratio and updates the configuration memory to identify the selected configuration. The selected configuration is then used by the audio sensor selector 210 to select the audio sensor that should pass the input to the media identifier 230.

In the examples disclosed herein, the example selection tester 240 periodically tests the signal-to-noise ratio of the configuration (e.g., every two minutes, every ten minutes, every hour, etc.). Periodic testing reduces the likelihood of missing media identification information as a result of a user changing the configuration of the audio output of the media presentation device 110. For example, if a user changes from a broadcast television input (perhaps using rear-facing speakers) to a Blu-ray Disc input (perhaps using a surround sound system), the configuration of the audio system may be modified. Furthermore, other changes in the environment may cause the media recognition performance of one audio sensor configuration to become better than another, such as, for example, opening a window, a different arrangement of furniture, or any other change in the media presentation environment 102 that may affect the ability of the media identifier 230 to identify media.

2 , the example selection tester 240 performs testing and/or analysis of the configured signal-to-noise ratio at the meter 114. However, such analysis may additionally or alternatively be performed at any other location, such as, for example, the central facility 190, a configuration device communicatively coupled to the meter 114, etc. In some examples, the central facility 190 performs analysis on audio collected by the various audio sensor configurations of the meter 114 and transmits the configuration information to the meter 114. In some examples, the central facility 190 may provide other configuration information and/or operating parameters to the meter 114, such as, for example, indications of which audio sensor configurations should be omitted from the analysis, threshold levels (e.g., the signal-to-noise ratio thresholds described below in conjunction with block 940 of FIG. 9 ), instructions regarding how often the testing and/or analysis will be performed, etc.

The example configuration interface 245 of the illustrated example of FIG2 receives configuration input from a user and/or installer of the meter 114. In some examples, the configuration interface 245 enables the user and/or installer to indicate an audio sensor configuration to be stored in the configuration memory 220 and used by the audio sensor selector 210. In some examples, the configuration interface 245 enables the user and/or installer to control other operating parameters of the meter 114, such as, for example, WiFi credentials to be used by the network communicator 260, setting family and/or group member identifiers, etc. In the illustrated example of FIG2, the configuration interface 245 is implemented by a low-power Bluetooth radio device. However, the configuration interface 245 can be implemented in any other manner, such as, for example, an infrared input, a universal serial bus (USB) connection, a serial connection, an Ethernet connection, etc. In some examples, the configuration interface 245 enables the meter 114 to be communicatively coupled to a media device, such as the media presentation device 110. This communicative coupling enables the configuration interface 245 to, for example, detect the audio configuration of the media presentation device 110 so that the configuration memory 220 can be updated to select the audio sensors 202, 204, 206, 208 that correspond to the selected audio configuration of the media presentation device 110. For example, if the media presentation device uses rear-facing speakers, an audio sensor that corresponds to a rear-facing microphone can be identified in the configuration memory 220.

2 receives media identification information (e.g., codes, signatures, etc.) from the media identifier 230 and audience identification data from the person identifier 270, and stores the received information in the data store 255. The example audience measurement data controller 250 periodically and/or aperiodically sends the audience measurement information stored in the data store 255 to the central facility 190 via the network communicator 260 to aggregate and/or prepare media monitoring reports.

The example data store 255 of the illustrated example of FIG2 can be implemented by any device for storing data, such as flash memory, magnetic media, optical media, etc. In addition, the data stored in the example data store 255 can have any data format, such as, for example, binary data, comma-delimited data, tab-delimited data, Structured Query Language (SQL) structures, etc. In this illustrated example, the example data store 255 stores media identification information collected by the media identifier 230 and audience identification data collected by the person identifier 270. In some examples, the example data store 255 additionally stores panelist demographic information so that user identifiers of received audience measurement data can be translated into demographic information before transmission to the central facility 190.

The example person identifier 270 of the illustrated example of FIG2 determines audience identification data representing the identities of audience members (e.g., panelists) present in the media presentation environment 102. In some examples, the person identifier 270 collects audience identification data by periodically or aperiodically prompting audience members in the media presentation environment 102 to identify themselves as present in the audience. Panelists can identify themselves by, for example, pressing a button on a remote control, speaking their name, etc. In some examples, the person identifier 270 prompts audience members to self-identify in response to one or more predetermined events (e.g., when the media presentation device 110 is turned on, the channel is changed, an infrared control signal is detected, etc.). The person identifier 270 provides the audience identification data to the audience measurement data controller so that the audience measurement data can be correlated with the media identification data to facilitate identification of which media is presented to which audience member.

The example network communicator 260 of the illustrated example of FIG2 transmits audience measurement information provided by the audience measurement data controller 250 (e.g., data stored in the data storage 255) to the central facility 190 of the audience measurement entity. In this illustrated example, the network communicator 260 is implemented by a WiFi antenna that communicates with a WiFi network hosted by the example gateway 140 of FIG1 . However, in some examples, the network communicator may additionally or alternatively be implemented by an Ethernet port that communicates via an Ethernet network (e.g., a local area network (LAN)). Although the example meter 114 transmits data to the central facility 190 via the example gateway 140 in the illustrated example of FIG1 , data may be sent to the central facility 190 in any other manner. For example, the network communicator 260 may be implemented by a cellular radio device, and the example gateway 140 may be a cellular base station. In some examples, the example gateway 140 may be omitted and the example network communicator 260 may send data directly to the central facility 190.

The example power receiver 280 of the illustrated example of FIG2 is implemented as a Universal Serial Bus (USB) socket and enables the meter 114 to be connected to a power source via a cable (e.g., a USB cable). In the examples disclosed herein, the media presentation device 110 has a USB port that provides power to an external device, such as the meter 114. In some examples, the media presentation device 110 can provide power to the external device via different types of ports, such as a High Definition Media Interface (HDMI) port, an Ethernet port, etc. The example power receiver 280 can be implemented in any manner to facilitate receiving power from the media presentation device 110 or any other power source (e.g., a wall outlet). In some examples, the power receiver 280 can additionally or alternatively facilitate diagnostic communications with the media presentation device 110. For example, the configuration interface 245 can communicate with the media presentation device 110 via the connection provided by the power receiver 280 (e.g., a USB port) to determine whether the media presentation device 110 is powered on, which input is being presented via the media presentation device 110, and which speakers the media presentation device 110 is using. In some examples, the connection is an HDMI connection, and configuration interface 245 communicates with media presentation device 110 using the HDMI Consumer Electronics Control (CEC) protocol.

The example battery 285 of the illustrated example of FIG2 stores electricity for use by the meter 114. The example battery 285 enables the meter 114 to operate when electricity is not supplied to the meter 114 via the power receiver 280. In the illustrated example of FIG2, the example battery is implemented using a lithium-ion battery. However, any other type of battery may be used additionally or alternatively. In the illustrated example of FIG2, the example battery 285 is rechargeable. Therefore, the example battery 285 can be charged while the meter 114 receives electricity via the power receiver 280 (e.g., while the media presentation device 110 is powered on) to facilitate the operation of the meter 114 when the meter 110 does not receive electricity via the power receiver 280 (e.g., while the media presentation device 110 is powered off). However, in some examples, the example battery 285 may be non-rechargeable.

FIG3 is an example front view of the example meter 114 of FIG1 and/or FIG2 . In the illustrated example of FIG3 , the example meter 114 includes a housing 310. In the examples disclosed herein, the housing 310 is attached to the media presentation device 110. For example, the housing can be attached to the top of the media presentation device 110, to the bottom of the media presentation device 110, to the side of the media presentation device 110, etc. In some examples, the housing 310 of the meter 114 is not attached to the media presentation device 110. For example, the housing 310 can be placed in any other location within the media presentation environment 102 so that audio can be received by the meter 114.

In the illustrated example of FIG3 , the example housing 310 includes an example left front opening 320 and an example right front opening 325. The front openings 320, 325 enable free-field audio in front of the housing to be received by the example audio sensors 202, 204, 206, 208 positioned toward the front of the meter 114. In the illustrated example of FIG3 , the front openings 320, 325 are symmetrically arranged on the front face of the meter 114. However, the front openings 320, 325 may be arranged in any other manner. Moreover, while two front openings 320, 325 are shown in the illustrated example of FIG3 , any other number of openings may additionally or alternatively be used. For example, there may be three openings on the front face of the housing 310, four openings on the front face of the housing 310, and so on.

FIG4 is an example rear view of the example meter 114 of FIG1 and/or FIG2 . In the illustrated example of FIG4 , the example housing 310 includes an example left rear opening 430 and an example right rear opening 435 . The rear openings 430 , 435 enable free-field audio at the rear of the housing 310 to be received by the example audio sensors 202 , 204 , 206 , 208 positioned toward the rear of the meter 114 . In the illustrated example of FIG4 , the rear openings 430 , 435 are symmetrically arranged on the rear of the meter 114 . However, the rear openings 430 , 435 may be arranged in any other manner. Moreover, while two rear openings 430 , 435 are shown in the illustrated example of FIG4 , any other number of openings may additionally or alternatively be used.

4 , housing 310 includes a USB port 440. In the illustrated example of FIG4 , USB port 440 enables USB cable 445 to connect power receiver 280 of FIG2 to an external power source (e.g., power provided by media presentation device 110). However, any other type and/or number of ports, cables, power sources, etc. may additionally or alternatively be used.

FIG5 is an example top view of the example meter 114 of FIG1 and/or FIG2 . In the illustrated example of FIG5 , front openings 320, 325 and rear openings 430, 435 are shown along the outline of housing 310. Within housing 310, an example circuit board 505 (e.g., a circuit board carrying example components of the example meter 114 of FIG2 ) is shown. In the illustrated example of FIG5 , a single circuit board 505 is shown. However, the example meter 114 may include multiple circuit boards so that components can be positioned to more efficiently utilize available space within housing 310.

5 , the first audio sensor 202 is connected to the circuit board 505 and is positioned adjacent to the left front opening 320. The second audio sensor 204 is connected to the circuit board 505 and is positioned adjacent to the right front opening 325. The third audio sensor 206 is connected to the circuit board 505 and is positioned adjacent to the left rear opening 430. The fourth audio sensor 208 is connected to the circuit board 505 and is positioned adjacent to the right rear opening 435. As a result, free-field audio passing through the openings 320, 325, 430, 435 of the housing 310 is picked up by the corresponding audio sensors 202, 204, 206, 208.

FIG6 is a diagram illustrating an example configuration of the media presentation environment 102 of FIG1 , in which rear-facing speakers are used. In the illustrated example of FIG6 , the media presentation device 110 is mounted to a wall 605 of the media presentation environment 102. However, in other examples, the media presentation device 110 may not be mounted to the wall 605, but may instead be, for example, placed on furniture within the media presentation environment 102, attached to the ceiling of the media presentation environment 102, or the like. In the illustrated example of FIG6 , the media presentation device 110 is positioned such that a display 610 of the media presentation device 110 faces the media presentation environment 102 (e.g., faces the room), such that the display 610 is viewable by the panelists 104 and 106.

In the illustrated example of FIG6 , media presentation device 110 utilizes rear-facing speakers 620, 625. In this example, the forward-facing audio sensors of meter 114 may not produce reliable identification of the media presented by media presentation device 110. In contrast, the rear-facing audio sensors of meter 114 may be more likely to produce reliable identification of the media presented by the media presentation device. In the illustrated example of FIG6 , rear-facing speakers 620, 625 are components of media presentation device 110. However, in some examples, speakers 620, 625 may be components of a separate media device, such as a soundbar, surround sound system, or the like.

FIG7 is a diagram illustrating an example configuration of the media presentation environment 102 of FIG1 , in which forward-facing speakers are used. As described above with respect to the example of FIG6 , the media presentation device 110 is mounted to a wall 605. However, in other examples, the media presentation device 110 may be positioned at any other location within the example media presentation environment 102. In contrast to the example of FIG6 , in the example of FIG7 , the media presentation device 110 utilizes forward-facing speakers 720, 725. In the example of FIG7 , the rear-facing audio sensor of the meter 114 may not produce reliable identification of the media presented by the media presentation device 110. However, the forward-facing audio sensor of the meter 114 is more likely to produce reliable identification of the media presented by the media presentation device. In the example of FIG7 , the forward-facing speakers 720, 725 are components of the media presentation device 110. However, in some examples, the speakers 720, 725 may be components of a separate media device, such as a soundbar, a surround sound system, or the like.

Fig. 8 is the figure of the example configuration of the media presentation environment 102 of expression Fig. 1, wherein used surround sound speaker system.In the illustrative example of Fig. 8, media presentation device 110 is installed to wall 605.Yet, in other examples, media presentation device 110 can be positioned at any other position in the example media presentation environment 102.In the illustrative example of Fig. 8, audio frequency is sent from surround sound speaker.In some examples, loudspeaker can be connected via for example audio/video receiver (for example, audio/video receiver 118 of Fig. 1) and media presentation device 110 communication ground.

In the illustrated example of FIG8 , the surround sound system includes a center channel speaker 810, a subwoofer 815, a left front channel speaker 820, a right front channel speaker 825, a left rear channel speaker 830, and a right rear channel speaker 835. In the illustrated example of FIG8 , the surround sound system is arranged in a 5.1 channel configuration. However, any other speaker configuration including any other number of speakers, any other type of speakers, and/or their arrangement may be used in addition or alternatively. For example, the surround sound speaker system may be arranged in a 7.1 surround sound configuration. In the illustrated example of FIG8 , variations in the placement of the surround sound system's speakers can produce different audio environments in which different configurations of the example meter 114's audio sensors can produce different levels of recognition of the media presented by the media presentation device 110. For example, if the center channel is positioned slightly behind the media presentation device (e.g., toward a wall), a rear-facing audio sensor may be more suitable. Furthermore, in the illustrated example of FIG8 , although a surround sound system with a 5.1 channel configuration is used, some media sources do not utilize all 5.1 channels. For example, when presenting broadcast television, the surround sound system may only present the media in a 2.1 format (e.g., the surround sound system may utilize the left front speaker 820, the right front speaker 825, and the subwoofer 815). In such a configuration, the forward-facing audio sensor of the meter 114 may be more effective in identifying the media being presented.

As shown in the illustrated examples of Figures 6, 7, and/or 8, different speaker configurations can be used within the media presentation environment 102. In the examples disclosed herein, the example meter 114 can be configured based on the speaker configuration of the media presentation environment 102. Moreover, in some examples, the speaker configuration can be changed during media presentation (e.g., when different media sources are selected for presentation by the media presentation device 110). To account for these changes in the acoustic environment, the example meter 114 periodically analyzes different configurations of the audio sensors to select the audio sensor configuration that produces the best recognition results.

Although an example manner of implementing the example meter 114 of FIG1 is illustrated in FIG2 , the processes and/or apparatus illustrated in FIG2 may be combined, divided, rearranged, omitted, eliminated, and/or implemented in any other manner. Furthermore, the example audio sensors 202 , 204 , 206 , 208 , the example audio sensor selector 210 , the example configuration memory 220 , the example media identifier 230 , the example selection tester 240 , the example configuration interface 245 , the example audience measurement data controller 250 , the example data storage 255 , the example network communicator 260 , the example person identifier 270 , the example power receiver 280 , the example battery 285 , and/or more generally the example meter 114 of FIG1 and/or FIG2 may be implemented in hardware, software, firmware, and/or any combination of hardware, software, and/or firmware. Thus, for example, any of the example audio sensors 202, 204, 206, 208, the example audio sensor selector 210, the example configuration memory 220, the example media identifier 230, the example selection tester 240, the example configuration interface 245, the example audience measurement data controller 250, the example data storage unit 255, the example network communicator 260, the example person identifier 270, the example power receiver 280, the example battery 285 and/or more generally the example meter 114 of Figures 1 and/or 2 can be implemented via one or more analog or digital circuits, logic circuits, programmable processors, application specific integrated circuits (ASICs), programmable logic devices (PLDs) and/or field programmable logic devices (FPLDs). When any of the apparatus or system claims of this patent are understood to cover purely software and/or firmware implementations, any of the example audio sensors 202, 204, 206, 208, the example audio sensor selector 210, the example configuration memory 220, the example media identifier 230, the example selection tester 240, the example configuration interface 245, the example audience measurement data controller 250, the example data storage 255, the example network communicator 260, the example person identifier 270, the example power receiver 280, the example battery 285 and/or more generally the example meter 114 of Figures 1 and/or 2 is thereby expressly defined as including a tangible computer-readable storage device or storage disk, such as a memory, digital versatile disk (DVD), compact disk (CD), Blu-ray disk, etc., that stores software and/or firmware. In addition, the example instrument 114 of Figures 1 and 2 may include one or more elements, processes and/or devices in addition to or instead of those illustrated in Figure 2, and/or may include more than one or all of any of the illustrated elements, processes and devices.

Flowcharts representing example machine-readable instructions for implementing the example meter 114 of FIG. 1 and/or FIG. 2 are shown in FIG. 9 , FIG. 10 , FIG. 11 , and/or FIG. 12 . In these examples, the machine-readable instructions comprise a program for execution by a processor, such as the processor 1412 shown in the example processor platform 1400 discussed below in conjunction with FIG. 14 . The program may be embodied in software stored on a tangible computer-readable storage medium, such as a CD-ROM, floppy disk, hard disk, digital versatile disk (DVD), Blu-ray disk, or memory associated with the processor 1412 , although the entire program and/or portions thereof can alternatively be executed by a device other than the processor 1412 and/or embodied in firmware or dedicated hardware. Furthermore, while the example program is described with reference to the flowcharts illustrated in FIG. 9 , FIG. 10 , FIG. 11 , and/or FIG. 12 , many other methods of implementing the example meter 114 may alternatively be used. For example, the order of execution of the blocks may be changed, and/or some of the blocks described may be changed, eliminated, or combined.

As mentioned above, the example processes of Figures 9, 10, 11, and/or 12 can be implemented using coded instructions (e.g., computer and/or machine-readable instructions) stored on a tangible computer-readable storage medium, such as a hard drive, flash memory, read-only memory (ROM), compact disk (CD), digital versatile disk (DVD), cache, random access memory (RAM), and/or any other storage device or storage disk in which information is stored for any duration (e.g., for an extended period of time, permanently, temporarily, temporarily buffering and/or caching information). As used herein, the term tangible computer-readable storage medium is expressly defined to include any type of computer-readable storage device and/or storage disk and to exclude propagating signals and to exclude transmission media. As used herein, "tangible computer-readable storage medium" and "tangible machine-readable storage medium" are used interchangeably. Additionally or alternatively, the example processes of Figures 9, 10, 11, and/or 12 may be implemented using coded instructions (e.g., computer and/or machine readable instructions) stored on a non-transitory computer and/or machine readable medium, such as a hard drive, flash memory, read-only memory, compact disk, digital versatile disk, cache, random access memory, and/or any other storage device or storage disk in which information is stored for any duration (e.g., for an extended period, permanently, temporarily, temporarily buffered, and/or cached information). As used herein, the term non-transitory computer readable medium is expressly defined to include any type of computer readable storage device and/or storage disk and excludes propagating signals and excludes transmission media. As used herein, when the phrase "at least" is used as a transitional term in the preamble of a claim, it is open ended in the same manner as the term "comprising" is open ended.

FIG9 is a flow diagram representing example machine-readable instructions 900 that may be executed to implement the meter of FIG1 and/or FIG2 to perform media identification using a selected audio sensor configuration. The example program 900 of the example example of FIG9 begins when the example audio sensor selector 210 identifies an audio sensor configuration stored in the configuration memory 220 (block 910). In the example of FIG9 , the audio sensor configuration is stored in the configuration memory 220 by, for example, the configuration interface 245 and/or the example selection tester 240. In the example disclosed herein, the example audio sensor configuration is represented using a binary value corresponding to each of the audio sensors 202, 204, 206, and 208. Thus, in the example of FIG9 , four bits of memory within the configuration memory 220 are used to represent the different configurations of the example audio sensors 202, 204, 206, and 208. However, the example audio sensor configurations may be stored in the example configuration memory in any other manner. For example, respective gain values corresponding to each of the audio sensors 202, 204, 206, 208 may be stored in the example configuration memory to, for example, enable the audio sensor selector 210 to apply the respective gain values to audio signals received via the example audio sensors 202, 204, 206, 208 (e.g., to increase/amplify audio signals received via the audio sensors, to reduce audio signals received via the audio sensors).

The example audio sensor selector 210 receives audio via the audio sensors 202, 204, 206, and 208 and combines the received audio (block 920). In the illustrated example of FIG. 9 , the received audio is mixed according to the audio sensor configuration retrieved from the configuration memory 220 in block 910. The combined audio is passed to the media identifier 230. The example media identifier 230 attempts to identify the media (block 930). When attempting to identify the media, the example media identifier 230 determines an identifier for the media (e.g., the value of the detected watermark/code) and a signal-to-noise ratio corresponding to the strength of the detected watermark/code. As noted above, while signal-to-noise ratio is used in the examples disclosed herein, any other quality metric may additionally or alternatively be used.

The example audience measurement data controller 250 checks the signal-to-noise ratio of the identified media to determine whether the signal-to-noise ratio is greater than a signal-to-noise ratio threshold (block 940). For example, if the signal-to-noise ratio of the determined media identifier is low (e.g., there is low confidence in the determined media identifier), the example audience measurement data controller 250 may discard the determined media identifier. Control then proceeds to block 910, where the example processing of blocks 910 through 940 is repeated. If the example audience measurement data controller 250 determines that the signal-to-noise ratio of the identified media is greater than the signal-to-noise ratio threshold (block 940 returns a "yes" result), the example audience measurement data controller 250 stores the determined media identifier in the data storage unit 255 (block 950). The example process 900 of the illustrated example of FIG. 9 is then continuously repeated to continuously attempt to identify media. As disclosed in conjunction with the illustrated example of FIG. 10, the media identifier may then be sent to the central facility 190 for inclusion in and/or preparation of a report summarizing media exposure.

FIG10 is a flow diagram representing example machine-readable instructions 1000 that may be executed to implement the example meter 114 of FIG1 and/or FIG2 to send media monitoring information to the example central facility 190 of FIG1 . The example program 1000 of FIG10 begins at block 1010 when the audience measurement data controller 250 determines whether a data storage threshold has been exceeded (block 1010). In this illustrated example, the threshold is a time limit that specifies that monitoring data be sent once per day. Additionally or alternatively, any other periodic and/or non-periodic method of sending monitoring information from the meter 114 may be used. For example, the data threshold may be based on the amount of monitoring information stored in the data storage 255.

If the threshold is not exceeded (block 1010 returns a "no" result), the audience measurement data controller 250 continues to determine whether the monitoring data threshold is exceeded. When the monitoring data threshold is exceeded (block 1010 returns a "yes" result), the audience measurement data controller 250 sends the stored monitoring information to the central facility 190 via the network communicator 260. In this illustrated example, the network communicator 260 sends the stored monitoring information via the gateway 140 and the network 180. However, in some examples, the network communicator 260 sends the stored network communications via a local connection such as, for example, a serial connection, a universal serial bus (USB) connection, a Bluetooth connection, etc. When the network communicator 260 sends via a local connection, the meter 114 can be physically moved to the location of the central facility 190 by, for example, physically mailing the meter 114.

FIG11 is a flowchart representing example machine-readable instructions that may be executed to implement the example meter of FIG1 and/or FIG2 to update a selected audio sensor configuration using input from the example configuration interface 245. The example process 1100 of the illustrated example of FIG11 begins when the example configuration interface 245 determines that the audio sensor configuration stored in the configuration memory 220 is to be updated (block 1110). If the audio sensor configuration is not to be updated (e.g., block 1110 returns a "no" result), the example configuration interface 245 continues to monitor for instructions to update the selected audio sensor configuration (block 1110). If the configuration interface 245 determines that the audio sensor configuration 220 is to be updated (block 1110 returns a "yes" result), the example configuration interface 245 collects input identifying a desired audio sensor configuration (block 1120). The example configuration interface 245 then updates the configuration memory 220 with the identified audio sensor configuration (block 1130).

In the illustrated example of Figure 11, the example configuration interface 245 can identify that the audio sensor configuration will be updated on a periodic basis. For example, the example configuration interface 245 can identify that the input should be read every five minutes. For example, the selector switch and/or jumper pins on the circuit board 505 of the example meter 114 can be set to select the rear audio sensor, can be set to select the front audio sensor, and/or can be set to select any other configuration of the audio sensor. In some examples, the input to the configuration interface 245 (e.g., selector switch, jumper pins, etc.) can be set by the installer when configuring the meter in the media presentation environment 102. Additionally or alternatively, the input to the configuration interface 245 can be set when the meter 114 is manufactured so that the meter can be easily installed by team members and/or users of the media presentation device without the need to configure the meter 114 and/or modify the switch and/or jumper pins.

In some examples, the configuration input received by the configuration interface 245 may be received via, for example, a wireless communication interface (e.g., via a Bluetooth connection to an external configuration device). In such an example, the example configuration interface 245 may determine that the audio sensor configuration is to be updated in response to the instruction received via the wireless communication interface (block 1110).

In some examples, the configuration input received by the configuration interface can be received directly from the media presentation device 110. For example, the configuration interface 245 can be communicatively coupled to the media presentation device via, for example, the power receiver 280. In such an example, the example configuration interface 245 can utilize a connection between the meter 114 and the media presentation device 110 via, for example, a USB cable, an HDMI cable, etc. In some examples, the configuration interface can query the media presentation device and/or can monitor information received from the media presentation device to identify the speaker configuration of the media presentation device 110. For example, if the configuration interface 245 detects that the media presentation device uses rear-facing speakers, the example configuration interface 245 can store a configuration corresponding to the rear-facing audio sensor in the configuration memory 220.

FIG12 is a flow diagram representing example machine-readable instructions 1200 that may be executed to implement the example meter of FIG1 and/or FIG2 to update a selected audio sensor configuration based on testing of different audio sensor configurations. The example process 1200 of the example illustrated example of FIG12 begins when the example selection tester 240 determines whether the selected audio sensor configuration stored in the configuration memory 220 is to be updated (block 1210). In the example illustrated example of FIG12, the example selection tester 240 determines whether the audio sensor configuration is to be updated periodically (e.g., every ten minutes, every hour, every day, etc.). However, the example selection tester 240 may determine whether the audio sensor configuration stored in the example configuration memory 220 is to be updated on a non-periodic basis (e.g., in response to an instruction received via the configuration interface 245). If the example selection tester 240 determines that the selected audio sensor configuration stored in the configuration memory 220 will not be updated (e.g., block 1210 returns a "no" result), the example process of block 1210 of Figure 12 is repeated until the selection tester 240 determines that the selected audio sensor configuration stored in the example configuration memory 220 will be updated.

If the example selection tester 240 determines that the audio sensor configuration stored in the configuration memory 220 is to be updated (e.g., block 1210 returns a "yes" result), the example selection tester 240 identifies the configuration of the example audio sensors 202, 204, 206, 208 to be tested (block 1220). In the example disclosed herein, there are four audio sensors 202, 204, 206, 208. Therefore, there are 15 possible configurations of the audio sensors. Example configurations of the audio sensors are shown in the example data table 1300 of the example of FIG. 13. For example, potential configurations may include a single audio sensor, a combination of any two audio sensors, a combination of any three audio sensors, or all four audio sensors. The example data table 1300 of the example of FIG. 13 includes an audio sensor configuration column 1310 and a signal-to-noise ratio column 1315. Although the signal-to-noise ratio column is shown in the example of FIG. 13, any other quality metric and/or combination of quality metrics may be used in addition or alternatively. The example data table 1300 of the illustrated example of FIG. 13 includes a row corresponding to each potential audio sensor configuration.

13 , audio sensor configuration column 1310 represents potential audio sensor configurations. In the example audio sensor configuration column 1310 , the first audio sensor 202 is identified by the letter A, the second audio sensor 204 is identified by the letter B, the third audio sensor 206 is identified by the letter C, and the fourth audio sensor 208 is identified by the letter D. However, any other nomenclature for naming potential configurations may additionally or alternatively be used.

13 , a first potential audio sensor configuration 1320 indicates a configuration that includes only the first audio sensor 202 (i.e., the left front microphone). A second potential audio sensor configuration 1322 indicates a configuration that includes only the second audio sensor 204 (i.e., the right front microphone). A third potential audio sensor configuration 1324 indicates a configuration that includes only the third audio sensor 206 (i.e., the left rear microphone). A fourth potential audio sensor configuration 1326 indicates a configuration that includes only the fourth audio sensor 208 (i.e., the right rear microphone).

A fifth potential audio sensor configuration 1328 indicates a configuration that includes a combination of the first audio sensor 202 and the second audio sensor 204 (i.e., two front microphones). A sixth potential audio sensor configuration 1330 indicates a configuration that includes the first audio sensor 202 and the third audio sensor 206 (i.e., a left front microphone and a left rear microphone). A seventh potential audio sensor configuration 1332 indicates a configuration that includes the first audio sensor 202 and the fourth audio sensor 208 (i.e., a left front microphone and a right rear microphone).

An eighth potential audio sensor configuration 1334 indicates a configuration that includes the first audio sensor 202, the second audio sensor 204, and the third audio sensor 206 (i.e., two front microphones and a left rear microphone). A ninth potential audio sensor configuration 1336 indicates a configuration that includes the first audio sensor 202, the second audio sensor 204, and the fourth audio sensor 208 (i.e., two front microphones and a right rear microphone). A tenth potential audio sensor configuration 1338 indicates a configuration that includes the first audio sensor 202, the third audio sensor 206, and the fourth audio sensor 208 (i.e., a left front microphone and two rear microphones).

An eleventh potential audio sensor configuration 1340 indicates a configuration that includes the second audio sensor 204 and the third audio sensor 206 (i.e., a right front microphone and a left rear microphone). A twelfth potential audio sensor configuration 1342 includes the second audio sensor 204 and the fourth audio sensor 208 (i.e., a right front microphone and a right rear microphone). A thirteenth potential audio sensor configuration 1344 indicates a configuration that includes the second audio sensor 204, the third audio sensor 206, and the fourth audio sensor 208 (i.e., a right front microphone and two rear microphones).

Fourteenth potential audio sensor configuration 1346 indicates a configuration that includes third audio sensor 206 and fourth audio sensor 208 (i.e., two rear microphones). Fifteenth potential audio sensor configuration 1348 indicates a configuration that includes first audio sensor 202, second audio sensor 204, third audio sensor 206, and fourth audio sensor 208 (i.e., all four microphones). While fifteen configurations of four microphones are shown in the illustrated example of FIG13 , any other configurations may be used additionally or alternatively and/or omitted. For example, configurations that use audio sensors located solely at opposite corners of the meter (e.g., sixth potential audio sensor configuration 1330, twelfth potential audio sensor configuration 1340) may be omitted because these configurations are unlikely to become the selected audio sensor configuration. Omitting these configurations reduces the amount of work performed when testing potential audio sensor configurations.

Returning to FIG. 12 , the example selection tester 240 selects a possible audio sensor configuration to test (block 1230 ). The example selection tester 240 collects signal-to-noise ratio information identified by the media identifier 230 while the audio sensor selector 210 is set to the audio sensor configuration to be tested (block 1240 ). The example selection tester 240 stores the signal-to-noise ratio in association with the selected audio sensor configuration (block 1250 ). As noted above, while the signal-to-noise ratio is used in the illustrated example of FIG. 12 , any other quality metric and/or combination of quality metrics may additionally or alternatively be used. As shown in the illustrated example of FIG. 13 , each audio sensor configuration (shown in the example audio sensor configuration column 1310 ) has a corresponding signal-to-noise ratio (shown in the example signal-to-noise ratio column 1315 ).

The example selection tester 240 determines whether there are additional possible audio sensor configurations to test (block 1260). If there are additional possible audio sensor configurations for testing (block 1260 returns a "yes" result), the example selection tester 240 continues to test the next selected audio sensor configuration until there are no more audio sensor configurations to be tested (block 1260 returns a "no" result). The example selection tester 240 selects the audio sensor configuration with the largest signal-to-noise ratio (block 1270). As shown in the illustrated example of FIG. 13, the fourteenth example audio sensor configuration 1346 has the largest signal-to-noise ratio. As a result, in the illustrated example of FIG. 13, the fourteenth example audio sensor configuration is selected.

In the illustrated example of FIG12 , the example selection tester 240 determines whether the signal-to-noise ratio of the selected audio sensor configuration is greater than a signal-to-noise ratio change threshold (block 1280). If the signal-to-noise ratio is not greater than the signal-to-noise ratio change threshold (block 1280 returns a “no” result), the example process of blocks 1210 through 1280 of FIG12 is repeated until the selection tester 240 determines that the signal-to-noise ratio of the identified configuration is greater than the signal-to-noise ratio change threshold (block 1280 returns a “yes” result). In response to determining that the signal-to-noise ratio of the selected audio sensor configuration is greater than the signal-to-noise ratio change threshold (block 1280 returns a “yes” result), the example selection tester 240 updates the configuration memory with the selected audio sensor configuration (block 1290). Utilizing the signal-to-noise ratio change threshold helps ensure that the audio sensor configuration is not inadvertently changed to a configuration that produces an insufficient level of media recognition.

The example process of FIG12 is then repeated to periodically and/or aperiodically update the configuration memory with the selected audio sensor configuration. Periodically updating the configuration memory ensures that if the audio environment changes (e.g., changing from using rear-facing speakers to using front-facing speakers), the audio sensor configuration is updated to account for the change in the audio environment.

14 is a block diagram of an example processor platform 1400 capable of executing the instructions of FIG 9 , FIG 10 , FIG 11 , and/or FIG 12 to implement the meter 114 of FIG 1 and FIG 2 . The processor platform 1400 may be, for example, a server, a personal computer, a mobile device (e.g., a cell phone, a smartphone, a tablet such as an iPad ^™ ), a personal digital assistant (PDA), an internet appliance, a DVD player, a CD player, a digital video recorder, a Blu-ray player, a game console, a personal video recorder, a set-top box, or any other type of computing device.

The processor platform 1400 of the illustrated example includes a processor 1412. The processor 1412 of the illustrated example is hardware. For example, the processor 1412 may be implemented by one or more integrated circuits, logic circuits, microprocessors, or controllers from any desired family or manufacturer.

The example processor 1412 includes a local memory 1413 (e.g., a cache). The example processor 1412 executes instructions to implement the example audio sensor selector 210, the example media identifier 230, the example selection tester 240, the example configuration interface 245, the example audience measurement data controller 250, and/or the example person identifier 270. The example processor 1412 communicates with a main memory including a volatile memory 1414 and a non-volatile memory 1416 via a bus 1418. The volatile memory 1414 can be implemented by synchronous dynamic random access memory (SDRAM), dynamic random access memory (DRAM), RAMBUS dynamic random access memory (RDRAM), and/or any other type of random access memory device. In the example of FIG. 14 , the volatile memory 1414 stores the configuration memory 220. However, any other memory device of the example processor platform 1400 can additionally or alternatively store the example configuration memory 220. The non-volatile memory 1416 may be implemented by flash memory and/or any other desired type of memory device.Access to the main memories 1414, 1416 is controlled by a memory controller.

The processor platform 1400 of the illustrated example also includes an interface circuit 1420. The interface circuit 1420 may be implemented by any type of interface standard, such as an Ethernet interface, a Universal Serial Bus (USB), and/or a PCI Express interface.

In the illustrated example, one or more input devices 1422 are connected to the interface circuit 1420. The input devices 1422 allow a user to enter data and commands into the processor 1412. The input devices may be implemented by, for example, an audio sensor, a microphone, a camera (still or video), a keyboard, buttons, a mouse, a touch screen, a trackpad, a trackball, an isopoint, and/or a voice recognition system. In the illustrated example of FIG14 , the example input devices 1422 implement the example audio sensors 202, 204, 206, 208.

One or more output devices 1424 are also connected to the interface circuit 1420 of the illustrated example. Output device 1424 may be implemented, for example, by a display device (e.g., a light emitting diode (LED), an organic light emitting diode (OLED), a liquid crystal display, a cathode ray tube display (CRT), a touch screen, a tactile output device, a printer, and/or a speaker). The interface circuit 1420 of the illustrated example thus typically includes a graphics driver card, a graphics driver chip, or a graphics driver processor.

The interface circuitry 1420 of the illustrated example also includes communication devices such as transmitters, receivers, transceivers, modems, and/or network interface cards to facilitate exchanging data with an external machine (e.g., any type of computing device) via a network 1426 (e.g., an Ethernet connection, a digital subscriber line (DSL), a telephone line, a coaxial cable, a cellular telephone system, etc.).

The illustrated example processor platform 1400 also includes one or more mass storage devices 1428 for storing software and/or data. Examples of these mass storage devices 1428 include floppy disk drives, hard disk drives, compact disk drives, Blu-ray disk drives, RAID systems, and digital versatile disk (DVD) drives.

The coded instructions 1432 of Figures 9, 10, 11, and/or 12 may be stored in a mass storage device 1428, in volatile memory 1414, in non-volatile memory 1416, and/or on a removable tangible computer-readable storage medium such as a CD or DVD. In the illustrated example of Figure 14, the example mass storage device 1428 stores the data storage 255. However, any other memory device of the example processor platform 1400 may additionally or alternatively store the example data storage 255.

Based on the above, it will be appreciated that the methods, apparatus, and articles disclosed above facilitate the selection of audio sensors and/or audio sensor combinations in an audience measurement device. In the examples disclosed herein, there are many different audio environments, and in some examples, the audio environment in which an audience measurement device (e.g., a meter) is to operate can be modified without being noticed. In the examples disclosed herein, the example audience measurement device accounts for these changing acoustic environments by enabling the selection of different audio sensor configurations corresponding to different acoustic environments. Moreover, the example audience measurement device enables testing of various configurations of audio sensors to enable the selection of a configuration of one or more audio sensors that produces reliable media identification. More reliable media identification results in fewer processor operations to detect and/or count media. For example, when media identification is more reliably obtained by the audience measurement device, it may not be necessary to perform error mitigation that would otherwise be performed (e.g., at a central facility of the audience measurement entity) to remove erroneous media identification.

The following additional examples are disclosed herein. The disclosed examples may be implemented individually and/or in one or more combinations.

Example 1 is directed to a method for performing audio sensor selection in an audience metering device, the method comprising: identifying a plurality of audio sensor configurations supported by the audience metering device; calculating, by executing instructions with a processor, a first quality metric of a first media identifier determined from first audio received via a first audio sensor configuration among the audio sensor configurations; calculating, by executing instructions with the processor, a second quality metric of a second media identifier determined from second audio received via a second audio sensor configuration among the audio sensor configurations; selecting, based on a comparison of the first quality metric and the second quality metric, one of the first audio sensor configuration among the audio sensor configurations or the second audio sensor configuration among the audio sensor configurations; and performing media monitoring at the audience metering device using the selected audio sensor configuration among the audio sensor configurations.

Example 2 includes the method of Example 1, further comprising storing the selected one audio sensor configuration in a configuration memory.

Example 3 includes the method of Example 1, wherein the selecting of the one of the first audio sensor in the audio sensor configuration or the second audio sensor in the audio sensor configuration is performed when at least one of the first quality metric or the second quality metric satisfies a quality metric change threshold.

Example 4 includes the method of any of Examples 1 to 3, wherein the first of the audio sensor configurations corresponds to at least one front-facing microphone.

Example 5 includes the method of any of Examples 1 to 3, wherein the first of the audio sensor configurations corresponds to at least one rear-facing microphone.

Example 6 includes the method of any of Examples 1 to 3, wherein the first of the audio sensor configurations corresponds to a combination of at least one front-facing microphone and at least one rear-facing microphone.

Example 7 includes the method of Example 1, wherein identifying the plurality of audio sensor configurations is performed periodically.

Example 8 includes the method of any of Examples 1 to 3, wherein the first quality metric is a signal-to-noise ratio.

Example 9 is directed to an apparatus for performing audio sensor selection, the apparatus comprising: at least two audio sensors for receiving audio at an audience metering device; and a selection tester for identifying a plurality of audio sensor configurations supported by the at least two audio sensors of the audience metering device, obtaining a first quality metric of a first media identifier corresponding to audio received via a first audio sensor configuration of the audio sensor configurations, obtaining a second quality metric of a second media identifier corresponding to audio received via a second audio sensor configuration of the audio sensor configurations, and selecting one of the first audio sensor configuration and the second audio sensor configuration based on a comparison of the first quality metric and the second quality metric. The example apparatus includes a media identifier for identifying audio received at the audience metering device using the selected one of the audio sensor configurations.

Example 10 includes the device of Example 9, further comprising a configuration memory for storing the selected one of the audio sensor configurations.

Example 11 includes the apparatus of Example 9, wherein the selection tester selects one of the first audio sensor configuration or the second audio sensor configuration when at least one of the first quality metric or the second quality metric satisfies a quality metric change threshold.

Example 12 includes the device of Example 9, further comprising: an audio sensor selector for combining audio received via a selected one of the first audio sensor configuration in the audio sensor configurations or the second audio sensor configuration in the audio sensor configurations to form a combined audio, the media identifier performing the recognition based on the combined audio.

Example 13 includes the device of any of Examples 9 to 12, wherein the first of the audio sensor configurations corresponds to at least one front-facing microphone.

Example 14 includes the device of any of Examples 9 to 12, wherein the first of the audio sensor configurations corresponds to at least one rear-facing microphone.

Example 15 includes the device of any of Examples 9 to 12, wherein the first of the audio sensor configurations corresponds to a combination of at least one front-facing microphone and at least one rear-facing microphone.

Example 16 includes the device of Example 9, wherein the identifying of the first one of the audio sensor configurations and the second one of the audio sensor configurations is performed periodically.

Example 17 includes the apparatus of any of Examples 9 to 12, wherein the first quality metric is a signal-to-noise ratio.

Example 18 is directed to a non-transitory computer-readable medium comprising instructions that, when executed, cause an audience metering device to at least identify a plurality of audio sensor configurations supported by the audience metering device, calculate a first quality metric of a first media identifier determined from first audio received via a first audio sensor configuration of the audio sensor configurations, calculate a second quality metric of a second media identifier determined from second audio received via a second audio sensor configuration of the audio sensor configurations, select one of the first audio sensor configuration of the audio sensor configurations or the second audio sensor configuration of the audio sensor configurations based on a comparison of the first quality metric and the second quality metric, and perform media monitoring at the audience metering device using the selected one of the audio sensor configurations.

Example 19 includes the non-transitory computer-readable medium of Example 18, wherein the instructions, when executed, further cause the audience metering device to store the selected audio sensor configuration in a configuration memory.

Example 20 includes the non-transitory computer-readable medium of Example 18, wherein the selecting of the one of the first audio sensor configuration or the second audio sensor configuration is performed when at least one of the first quality metric or the second quality metric satisfies a quality metric change threshold.

Example 21 includes the non-transitory computer-readable medium of any of Examples 18 to 20, wherein the first of the audio sensor configurations corresponds to at least one front-facing microphone.

Example 22 includes the non-transitory computer-readable medium of any of Examples 18 to 20, wherein the first of the audio sensor configurations corresponds to at least one rear-facing microphone.

Example 23 includes the non-transitory computer-readable medium of any of Examples 18 to 20, wherein the first of the audio sensor configurations corresponds to a combination of at least one front-facing microphone and at least one rear-facing microphone.

Example 24 includes the non-transitory computer-readable medium of Example 18, wherein the identifying of the plurality of audio sensor configurations is performed periodically.

Example 25 includes the non-transitory computer-readable medium of any of Examples 18 to 20, wherein the first quality metric is a signal-to-noise ratio.

Example 26 is directed to an apparatus for performing audio sensor selection, the apparatus comprising: at least two audio sensing devices for receiving audio at an audience metering device; and a selection test device for identifying a plurality of audio sensor configurations supported by the at least two audio sensors of the audience metering device, obtaining a first quality metric of a first media identifier corresponding to audio received via a first audio sensor configuration of the audio sensor configurations, obtaining a second quality metric of a second media identifier corresponding to audio received via a second audio sensor configuration of the audio sensor configurations, and selecting one of the first audio sensor configuration of the audio sensor configurations or the second audio sensor configuration of the audio sensor configurations based on a comparison of the first quality metric and the second quality metric. The example apparatus includes a media identification device for identifying the audio received at the audience metering device using the selected one of the audio sensor configurations.

Example 27 includes the apparatus of Example 26, further comprising a configuration memory device for storing the selected one of the audio sensor configurations.

Example 28 includes the apparatus of Example 26, wherein the selection test device selects the one of the first one of the audio sensor configurations or the second one of the audio sensor configurations when at least one of the first quality metric or the second quality metric satisfies a quality metric change threshold.

Example 29 includes the device described in Example 26, which further includes: an audio sensor selection device, which is used to combine audio received via a selected one of the first audio sensor configuration in the audio sensor configuration or the second audio sensor configuration in the audio sensor configuration to form a combined audio, and the media recognition device performs the recognition based on the combined audio.

Example 30 includes the device of any of Examples 26 to 29, wherein the first of the audio sensor configurations corresponds to at least one front-facing microphone.

Example 31 includes the device of any of Examples 26 to 29, wherein the first of the audio sensor configurations corresponds to at least one rear-facing microphone.

Example 32 includes the device of any of Examples 26 to 29, wherein the first of the audio sensor configurations corresponds to a combination of at least one front-facing microphone and at least one rear-facing microphone.

Example 33 includes the device of Example 26, wherein the identifying of the first one of the audio sensor configurations and the second one of the audio sensor configurations is performed periodically.

Example 34 includes the apparatus of any of Examples 26 to 29, wherein the first quality metric is a signal-to-noise ratio.

Although certain example methods, apparatus, and articles of manufacture have been disclosed herein, the scope of coverage of this patent is not limited thereto. On the contrary, this patent covers all methods, apparatus, and articles of manufacture fairly falling within the scope of the claims of this patent.

Claims (34)

1. A method for performing audio sensor selection in an audience metering device, the method comprising the steps of: The system identifies multiple audio sensor configurations supported by the audience metering device, the multiple audio sensor configurations being configured to configure multiple audio sensors at the audience metering device, the multiple audio sensor configurations identifying different combinations of the multiple audio sensors, the multiple audio sensor configurations including a first audio sensor configuration and a second audio sensor configuration; By utilizing processor instructions, a first quality metric is calculated to determine a first media identifier based on a first audio received via the first audio sensor configuration. By utilizing the processor to execute instructions, a second quality metric is calculated for the second media identifier determined from the second audio received via the second audio sensor configuration; Based on a comparison of the first quality metric and the second quality metric, one audio sensor configuration is selected from the first audio sensor configuration and the second audio sensor configuration, wherein the selected audio sensor configuration has the highest quality metric; and Media monitoring is performed at the audience metering device using the selected audio sensor configuration. 2. The method of claim 1, further comprising: storing the selected audio sensor configuration in a configuration memory. 3. The method of claim 1, wherein when at least one of the first quality metric and the second quality metric satisfies a quality metric change threshold, the selection of one of the first audio sensor configuration and the second audio sensor configuration is performed, wherein the quality metric of the selected audio sensor configuration satisfies the quality metric change threshold. 4. The method according to any one of claims 1 to 3, wherein the first audio sensor configuration corresponds to at least one forward-facing microphone. 5. The method according to any one of claims 1 to 3, wherein the first audio sensor configuration corresponds to at least one rear-facing microphone. 6. The method according to any one of claims 1 to 3, wherein the first audio sensor configuration corresponds to a combination of at least one forward microphone and at least one rear microphone. 7. The method of claim 1, wherein the identification of the plurality of audio sensor configurations is performed periodically. 8. The method according to any one of claims 1 to 3, wherein the first quality metric is a signal-to-noise ratio. 9. A device for performing audio sensor selection, the device comprising: At least two audio sensors receive audio at the audience metering device; Select the tester, which is used for: The system identifies multiple audio sensor configurations supported by the at least two audio sensors of the audience metering device, the multiple audio sensor configurations being configured to configure the at least two audio sensors at the audience metering device, the multiple audio sensor configurations identifying different combinations of the at least two audio sensors, the multiple audio sensor configurations including a first audio sensor configuration and a second audio sensor configuration; Obtain a first quality metric corresponding to a first media identifier received via the first audio sensor configuration; Obtain a second quality metric corresponding to a second media identifier received via the second audio sensor configuration; and Based on a comparison of the first quality metric and the second quality metric, one audio sensor configuration is selected from the first audio sensor configuration and the second audio sensor configuration, wherein the selected audio sensor configuration has the highest quality metric; and A media identifier is used to identify audio received at the audience metering device using a selected audio sensor configuration. 10. The device of claim 9, further comprising a configuration memory for storing a selected audio sensor configuration. 11. The device of claim 9, wherein when at least one of the first quality metric and the second quality metric satisfies a quality metric change threshold, the selection tester selects one of the first audio sensor configuration and the second audio sensor configuration, wherein the quality metric of the selected audio sensor configuration satisfies the quality metric change threshold. 12. The device of claim 9, further comprising: an audio sensor selector for combining audio received via a selected audio sensor configuration to form a combined audio, the media recognizer performing the recognition based on the combined audio. 13. The device according to any one of claims 9 to 12, wherein the first audio sensor configuration corresponds to at least one forward-facing microphone. 14. The device according to any one of claims 9 to 12, wherein the first audio sensor configuration corresponds to at least one rear-facing microphone. 15. The device according to any one of claims 9 to 12, wherein the first audio sensor configuration corresponds to a combination of at least one forward microphone and at least one rearward microphone. 16. The device of claim 9, wherein the identification of the plurality of audio sensor configurations is performed periodically. 17. The device according to any one of claims 9 to 12, wherein the first quality metric is a signal-to-noise ratio. 18. A non-transitory computer-readable medium comprising instructions that, when executed, cause a spectator measuring device to at least: The system identifies multiple audio sensor configurations supported by the audience metering device, the multiple audio sensor configurations being configured to configure multiple audio sensors of the audience metering device, the multiple audio sensor configurations identifying different combinations of the multiple audio sensors, the multiple audio sensor configurations including a first audio sensor configuration and a second audio sensor configuration; Calculate a first quality metric for a first media identifier determined from the first audio received via the first audio sensor configuration; Calculate a second quality metric for the second media identifier determined from the second audio received via the second audio sensor configuration; Based on a comparison of the first quality metric and the second quality metric, one audio sensor configuration is selected from the first audio sensor configuration and the second audio sensor configuration, wherein the selected audio sensor configuration has the highest quality metric; and Media monitoring is performed at the audience metering device using the selected audio sensor configuration. 19. The non-transitory computer-readable medium of claim 18, wherein, when executed, the instructions further cause the audience metering device to store the selected audio sensor configuration in a configuration memory. 20. The non-transitory computer-readable medium of claim 18, wherein when at least one of the first quality metric and the second quality metric satisfies a quality metric change threshold, selection of one of the first audio sensor configuration and the second audio sensor configuration is performed, wherein the quality metric of the selected audio sensor configuration satisfies the quality metric change threshold. 21. The non-transitory computer-readable medium according to any one of claims 18 to 20, wherein the first audio sensor configuration corresponds to at least one forward-facing microphone. 22. The non-transitory computer-readable medium according to any one of claims 18 to 20, wherein the first audio sensor configuration corresponds to at least one rear-facing microphone. 23. The non-transitory computer-readable medium according to any one of claims 18 to 20, wherein the first audio sensor configuration corresponds to a combination of at least one forward microphone and at least one rearward microphone. 24. The non-transitory computer-readable medium of claim 18, wherein the identification of the plurality of audio sensor configurations is performed periodically. 25. The non-transitory computer-readable medium according to any one of claims 18 to 20, wherein the first quality metric is a signal-to-noise ratio. 26. An audio sensor selection device, the audio sensor selection device comprising: A unit for identifying a plurality of audio sensor configurations supported by at least two audio sensing devices at a spectator metering device, the plurality of audio sensor configurations being configured to configure the at least two audio sensing devices at the spectator metering device, the plurality of audio sensor configurations identifying different combinations of the at least two audio sensing devices, the plurality of audio sensor configurations including a first audio sensor configuration and a second audio sensor configuration; A unit for obtaining a first quality measure of a first media identifier corresponding to the audio received via the first audio sensor configuration; A unit for obtaining a second quality metric corresponding to a second media identifier received via the second audio sensor configuration; and A unit for selecting one audio sensor configuration from the first and second audio sensor configurations based on a comparison of the first and second quality metrics, wherein the selected audio sensor configuration has the highest quality metric; and A unit for identifying audio received at the audience metering device using a selected audio sensor configuration. 27. The audio sensor selection device of claim 26, further comprising a unit for storing the selected audio sensor configuration. 28. The audio sensor selection device of claim 26, wherein when at least one of the first quality metric and the second quality metric satisfies a quality metric change threshold, the unit for selecting one audio sensor configuration of the first audio sensor configuration and the second audio sensor configuration selects one audio sensor configuration of the first audio sensor configuration and the second audio sensor configuration, wherein the quality metric of the selected audio sensor configuration satisfies the quality metric change threshold. 29. The audio sensor selection device of claim 26, further comprising a unit for combining audio received via the selected audio sensor configuration to form a combined audio, wherein the unit for identifying the audio received at the audience metering device performs the identification based on the combined audio. 30. The audio sensor selection device according to any one of claims 26 to 29, wherein the first audio sensor configuration corresponds to at least one forward-facing microphone. 31. The audio sensor selection device according to any one of claims 26 to 29, wherein the first audio sensor configuration corresponds to at least one rear-facing microphone. 32. The audio sensor selection device according to any one of claims 26 to 29, wherein the first audio sensor configuration corresponds to a combination of at least one forward microphone and at least one rearward microphone. 33. The audio sensor selection device of claim 26, wherein the unit for identifying the plurality of audio sensor configurations supported by the at least two audio sensing devices at the audience metering device periodically performs the identification of the plurality of audio sensor configurations. 34. The audio sensor selection device according to any one of claims 26 to 29, wherein the first quality metric is a signal-to-noise ratio.