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WO2001077846A1 - Systeme expert destine a la generation de listes d'ecoute - Google Patents

Systeme expert destine a la generation de listes d'ecoute Download PDF

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Publication number
WO2001077846A1
WO2001077846A1 PCT/US2001/011106 US0111106W WO0177846A1 WO 2001077846 A1 WO2001077846 A1 WO 2001077846A1 US 0111106 W US0111106 W US 0111106W WO 0177846 A1 WO0177846 A1 WO 0177846A1
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WIPO (PCT)
Prior art keywords
pieces
attributes
piece
computer
library
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PCT/US2001/011106
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English (en)
Inventor
Nick Wilson
Mick Lord
Bernadette Curran
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AEI MUSIC NETWORK Inc
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AEI MUSIC NETWORK Inc
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Priority to AU2001251347A priority Critical patent/AU2001251347A1/en
Publication of WO2001077846A1 publication Critical patent/WO2001077846A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K15/00—Acoustics not otherwise provided for
    • G10K15/04—Sound-producing devices
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K15/00—Acoustics not otherwise provided for
    • G10K15/02—Synthesis of acoustic waves

Definitions

  • the expert divides the pieces into a number of types or genres and provides a default set of sequence selection rules.
  • the music programmer selects a single genre or a sequence of genres for time slots during the day, perhaps varying by day of the week or day of the year, and adjusts the sequence selection rules.
  • the system then automatically selects pieces within the specified genre either randomly or according to which piece has not been played for the longest time or with weighting to play certain pieces more often and, in addition, applies sequence selection rules.
  • the sequence selection rules include:
  • Pieces of the same style may be separated with a maximum number to be played in a row or a number of minutes between songs of the style or number of song positions between songs of the style.
  • Energy Level Each piece is designated as having an energy level. The programmer can specify that pieces of a certain energy level will have a maximum number in a row or a certain number of minutes between them or a certain number of positions between them.
  • Each piece is designated as having a mood level.
  • the programmer can specify that pieces of a certain mood level will have a maximum number in a row or a certain number of minutes between them or a certain number of positions between them.
  • Time Slots The programmer can flag certain pieces such that they will not be played during certain time slots of the day or certain days of the week or certain days of the year.
  • Each piece can be designated as relating to a certain theme, such as Christmas music.
  • the programmer can specify that only pieces of a certain theme will be played.
  • an expert programmer must be employed to specify all of the pieces for each play list for each part of the day.
  • the expert is then practicing an art that is highly particular to the individual expert.
  • the expert applies his or her knowledge of the characteristic of the intended audience and the intended ambiance for the establishment as well as the time of the day and the day of the week, along with an artistic sense of which pieces should follow which other pieces to produce a pleasing sequence that meets the client's objectives.
  • the invention is a system and method for delivering audio visual content to customers for playing to audiences. It uses expert system components to leverage the skills of music programmers to serve many clients through the system rather than requiring hands on attention by a music programmer to every song on every play list.
  • the expert system By assigning for each part of the day, for each zone, for each customer establishment, attributes which identify the target audience and the character of the establishment selected from a long list of possible attributes, the expert system is able to identify pieces of music appropriate for that particular situation.
  • the pieces are not selected based on "genres” like in the prior art systems. They are selected based on whether their characteristics (attributes assigned by an expert) satisfy a definition of a "stream".
  • Each piece of music (or video or text or other material) can typically be placed in many different streams. One stream might focus on the instruments used in the piece, while another stream focuses on the composer, while another stream focuses on the style, while another stream focuses on the artist, while another stream focuses on the period, et cetera.
  • an expert defines a boolean specifier for each stream, as described above, along with playback rules to be applied when the system at the client premises selects pieces to be played.
  • the expert specifies a sequence of streams, a "stream order", whereby one piece from each steam in the sequence is played in turn and then the sequence is repeated.
  • the specified stream order makes up a "scenario”. While defining a stream order for the scenario, the expert also specifies additional playback rules associated with the scenario and weightings for use by the expert systems to choose a scenario for a particular target audience.
  • the expert system which selects pieces for a particular target audience is operated by assigning to the audience one or more attributes characterizing the audience selected from a long list of possible audience / establishment attributes.
  • the selected attributes are stored in a memory associated with an identification of the target audience for the client.
  • An expert has previously assigned weightings to each of many scenarios, each scenario effectively comprising a set of pieces out of the master library which match the boolean specifiers of each stream within the scenario.
  • the expert has assigned positive weightings to selected ones of the attributes from the set of possible audience / establishment attributes which indicates that the expert believes the scenario is suitable for an audience characterized by that attribute.
  • the list of attributes which are positively weighted by the expert is stored in a computer memory associated with the scenario (set of pieces).
  • the computer selects scenarios which have positive weightings which have been generated from the attributes which matches the attributes associated with the audience. Totals of the positively weighted attributes are computed and the scenario with the highest total is selected.
  • the scenario now specifies which pieces out of a library of pieces are suitable for the target audience.
  • the system can be used with a large library to select pieces specified by the previously designated stream order for performing the scenario.
  • the entire library of pieces is much too large to provide at a customer site and it is impractical to provide a constantly operating data link between the customer site and the immense master library. Therefore, the boolean specifiers within the scenario are used to select pieces from the master library to make up a subset library (client library) from which the pieces are to be selected for presentation.
  • each of the pieces in the master library has been assigned one or more attributes characterizing the piece selected from a list of possible attributes, and the list of attributes was stored in the master library associated with an identification of the piece.
  • the system therefore operates by selecting for a subset library piece identifiers from the master library which are associated with attributes that satisfy one or more of the boolean specifiers of the various streams which make up the scenario.
  • the stream order of the scenario is consulted and the boolean specifier for each stream is used for selecting the pieces in proportion to a relative number of times the stream appears within the stream order of the scenario.
  • the subset library When the subset library is created, it is downloaded to the client's system, either by a computer to computer connection or by distribution of a recording medium such as a CD-ROM or DVD.
  • the client's system then operates by using an expert system based on the previously designated playback rules to choose pieces from the subset library for playing at each point in time.
  • the playback rules can operate on any of the piece attributes to prohibit the playing of a piece with a specified attribute more than n times in succession, or more than n times within a specified time period, or following a piece that has another specified attribute within a specified time, or to force a piece with attribute 'A' to follow a piece with attribute 'B' ('A' and 'B' can represent the same attribute).
  • This allows the very attractive feature that the ending of a piece, which is entered into the system as one of the piece attributes, can be used to select or avoid a certain type of beginning for the following piece, to create a pleasant flow from one piece to another for the audience.
  • Figure 1 shows the System Overview.
  • Figure 2 shows the process of building the Master Library.
  • Figure 3 shows the relational database structure of the Master Piece
  • Figure 4 shows the relational database structure for the Scenario Database.
  • Figure 5 shows how the Scenario Expert System selects the Scenario for each zone and Daypart to assemble a SoundScape for each zone with one Scenario for each Daypart.
  • Figure 6 shows the data structure of Soundscapes as held on each Client Machine.
  • the items to be played for an audience by the system may be pieces of any type, including music, other audio, video, still image pieces, or text pieces. Because the most common application is music and pieces of music are commonly referred to as "songs", in this document, each piece may be referred to as a "song”.
  • the system is comprised of a Master System 1 operated by the company that provides the music or other pieces and a large number of Client Systems 2 operated by the clients.
  • the clients are commercial establishments providing background music, or music with video, or a series of still images for viewing by a target audience, typically customers of the client.
  • the components of the Client System 2 include an audio or video play back system for playing each piece, step 14.
  • the remaining hardware components of each Client System are typically general purpose computer components for storing the pieces in digital form and storing the set of rules and other data which drive the selection of the pieces, step 13.
  • the Client System includes a large memory containing a Client Piece Library 12 of pieces to be played.
  • the system is usually implemented with the Client Piece Library stored in digital form on a hard disk. However, it can equally be implemented with storage on optical disks such as CDs or with analog media such as videotape or with film transparencies for showing with a slide projector.
  • the final component of the Client System is a memory, which stores the SoundScape data 11 which is a set of rules for operating the Expert Selection System in step 13.
  • the Master System 1 operated by the content provider includes a Master Piece Database 5.
  • This database is typically stored in digital format in a large set of hard disks. Alternatively, the pieces may be stored on optical disks or analog videotape.
  • the Master System automatically selects pieces from the Master Piece Database 5 for download to each client based on Soundscapes selected for the client, step 8. The Soundscapes in turn are selected by a Scenario Expert System, step 7.
  • the Scenario Expert System receives input from a Scenario Database with Expert Weightings for each scenario 3 and from Attributes relating to the client and the client audience 4.
  • the Master Piece Database 5 and the Scenario Database 3 together make up the Master Library 6.
  • Figure 2 shows the process of building the Master Piece Database 5.
  • descriptive information for each piece is added, consisting of: an identification number for each piece, a group identification number which specifies an identification for the artist or group of artists, the artist's name, and the title of each piece.
  • a human expert listens to (or views) each piece to determine which Attributes from a standard list of possible Piece Attributes 22 should be assigned to the piece, step 23.
  • An example of the standard Piece Attributes which illustrates all of the types of attributes of the preferred embodiment but has been edited to delete some redundancy of attribute types, is shown in Table 1 below.
  • the structure of the Master Piece Database is shown in Figure 3.
  • the structure includes an Artist Table 41, which relates each artist name to a group identifier. It also includes a Piece Table 42 with a one- to-many relationship from the Group ID in the Artist Table to the Group ID in the Piece Table.
  • the primary index for the Piece Table is a Piece ID.
  • This table also includes, for each Piece ID, the name of the file in which the piece content is stored as well as the title of the piece.
  • the Piece ID of the piece table is related by a one- to-many relationship to a Joining Table 43 which, for each Piece ID, specifies a Node ID.
  • Each Node ID of the joining table is related with a many-to-one relationship to a Node ID that is the primary key of an Attribute Tree Table 44.
  • the Attribute Tree Table specifies a Description and potentially a Parent Node ID .
  • the Parent Node ID specifies a many-to-one relationship with each Node ID. This is required because certain generic attributes, such as "Pop” include many sub- “attributes such as “Top Forty”, “Acoustic Base Pop", and “Soft Rock” as shown in Table 1.
  • each sub-attribute implies each of the higher level attributes up the tree.
  • an expert begins by identifying many different "Streams"26, each of which specifies a type or character of music.
  • the Streams are each defined by a Boolean Specifier specifying the set of pieces that have or do not have attributes selected from the list of Piece Attributes, step 25.
  • the Boolean Specifier for one of the Streams will have an ending with a particular sound, a particular emotive appeal to the music, and a particular set of instruments. All of the customary Boolean set operations are possible, including union, intersection, and subtraction, with grouping of operations using parentheses to specify the order of operations.
  • Each of the possible Piece Attributes can be used to specify sets in the Boolean Specifier.
  • Each Stream 26 consists of Playback Rules, if any (described below), and a single Boolean Specifier comprised of Piece Attributes, Boolean operators, and parentheses.
  • each Scenario the expert specifies a sequence of Streams to be repeated, step 31 , and writes Playback Rules (described below) to be used in selecting the Scenario.
  • the repetition of Streams is typically in a pattern such as ABACABAD, where A,B,C, and D each specify a Stream by its identifier.
  • This pattern is stored in the Scenario Clock Table 56 in Figure 4.
  • a Database of Scenarios 3 is assembled.
  • a Current Attribute This is used to determine if the rule is to take effect to exclude a piece.
  • the rule is only active if the currently selected potential song (which was selected at random from the songs of the designated Stream that have not yet been played) has a Piece Attribute matching the Current Attribute.
  • a Target Attribute This is a Piece Attribute that is searched for in pieces that have already been played since the list of played pieces was last reset to zero.
  • a rule can specify one of the following three possibilities a. If the current potential song is selected, then the Target Attribute will have occurred more than n times in succession. b. If the current potential song is selected, then the Target Attribute will have occurred twice within a specified time period n. c. If the current potential song is selected, then the piece immediately before it does not have the Target Attribute. 4) A Value: When n is used in the rule, this value is used for n.
  • each rule therefore acts in a negative or exclusionary way.
  • the system can be modified to work with positive rules such as: a song with beginning ("intro") Y shall follow a song with ending X.
  • the database structure to store the Scenario Database is shown in Figure 4. This is a component of the Master Library 5.
  • the Scenario is named in the Scenario Table 54.
  • Each Scenario can have a number of Attributes attached to it in the Scenario Attributes Table 53, these attributes are assigned by a music specialist as part of step 31 from the list of Audience / Establishment Attributes 29 to show who the scenario is intended for.
  • the definitions of the attributes are copied from the list 29 and held in the Attribute Definition Table 58.
  • each record in the Attribute Definition Table 58 contains a reference to the node above it (its parent). If the ParentNodelD does not contain a valid value (usually represented by NULL in a relational database, or possibly an invalid value, like a negative number) then that Node is considered to be the root item of a tree.
  • weightings to be used as part of the selection process are calculated based on the attributes selected by the music specialist.
  • the weightings are calculated in the following manner. First, a seed weighting is assigned to all of the attributes that the music specialist has selected. This seed weighting is simply an arbitrary number, preferably 5.
  • the system will then attach weightings to all other attributes in the list of Audience / Establishment Attributes 29 by following the following steps: 1. All parent nodes that do not have a weighting assigned to them by the music specialist are assigned a number that is one less than the weighting number given to any child. 2. All child nodes are given the same weighting number as a parent unless they already have a weighting assigned by the music specialist.
  • the following is an example of a part of the attribute tree with weightings assigned as stored in the Attribute Tree Table 44.
  • the bold numbers are the seed weightings.
  • the italic numbers are the calculated weightings. I n this e xample, we have used 5 as the seed weighting.
  • a Scenario also has a Clock associated with it.
  • a Clock defines the ordering of Stream playback.
  • Each element of the Clock is stored in the ScenarioClock table 56.
  • Each Stream is defined as a Boolean Expression used by the system to select pieces, and it is defined in the Stream Table 57.
  • a Rules Table 55 allows a number of rules to be attached to each Scenario and Stream. This is achieved by having a column "ApplyTo" which identifies whether the value "ApplyTolD" refers to either a Scenario or a Stream.
  • the Rules Table 55 also includes two references to the Attribute Definition Table 58 to represent the Current Attribute and the Target Attribute.
  • the Rule Type column identifies which of the three rule types this rule belongs to (3a or 3b or 3c above), and the Value provides the n value for the Rule. Operation of the Scenario Selection Expert System The final input to the Scenario Selection Expert System 7 is the set of client
  • a client will have more than one zone that requires media playback, for example, a client may have a restaurant and a bar and a requirement for playing music with a family feel in the restaurant and more adult music in the bar.
  • Each zone is provided with a different SoundScape. For the purposes of system operation, each zone is effectively treated as a separate client.
  • the client attribute collection is selected by a sales person for the content provider touring the target establishment or asking the proprietor of the establishment a long series of questions. From this interview, the sales person will select a number of Attributes from the establishment attribute tree shown in Table 2 which accurately describe both the client and the client's target audience demographic. These are then input into the expert system that will pick applicable scenarios for the client. This is a simple procedure that is performed by searching all scenarios and calculating a sum of weighting for each scenario for each node of the attribute tree that has been selected as describing the customer site. The scenarios with the largest totals are presumed to be the most applicable for that client. The expert also constructs any Playback Rules that are appropriate for the particular SoundScape.
  • a SoundScape there may be different times of the day when the pieces to be presented should be selected to correspond with the time. For example, if a Scenario is intended for a restaurant, the lunchtime music might be quite different from the after work music.
  • the objective of the system is to create a different "Scenario" for each time of day ("Daypart"65). As shown in Figure 5, there is one Scenario for each Daypart, and all of the Scenarios together with the dayparting information and Playback Rules for the SoundScape, if any, make up a SoundScape 67.
  • the music specification that is provided to a client consists of one SoundScape for each zone.
  • Each SoundScape is made up of one Scenario for each Daypart and Playback Rules, if any.
  • each Scenario consists of an ordered sequence of Streams and Playback Rules, if any.
  • a Stream consists of a Boolean Specifier for the Stream specifying a set of desired Attributes and undesired Attributes and an optional set of Playback Rules.
  • the Stream, the Scenario and the SoundScape are generic as to a type of music. They do not specify particular pieces but only specify the character of the music to be played.
  • each SoundScape is made up of one or more Scenarios; each Scenario is made up of one or more Streams; each Stream is made up of a Boolean Specifier; and each of these items can have an optional set of Playback Rules.
  • the selection of a Scenario for a daypart is done based on the client specified criteria for the desired clientele during that daypart. If there is no good match between the pre created Scenarios and the client's requirements automatically generated by the Weightings, then the request is passed on to a music consultant employed by the content provider who will create a Scenario specifically for that client's demographic.
  • the system takes the attributes attached to all the scenarios and generates weightings for every tree node as described earlier. Then, for each corresponding node that has been selected as describing the client, the weights are totaled. The higher the total, the more appropriate the given scenario.
  • An ideal score would be one that is calculated to be the seed weight multiplied by the number of attributes attached to a customer. This would indicate that the Scenario matched point for point the attributes attached to the customer.
  • the human musical specialist would examine the request and determine if:
  • the final part of the Master System is a component that is responsible for selecting pieces for download to the client 8.
  • This component looks at the Scenario selected by the expert system for the client (or zone) and uses that as a guide for selecting pieces from the Master Piece Database, along with a record of pieces sent to the client in the past and Negative Filters provided by the client, to select the pieces for download.
  • Negative Filters for the client are also identified by the sales person during the same tour or interview when the attributes are identified.
  • a Negative filter allows a client to specify that they do not want a specific type of music. For example, if the system had recommended a mixture of 60's and 70's music, and the client had said they did not want to hear any Carpenters music for personal reasons, this allows the system to construct a SoundScape without having a music specialist create a new client specific Stream or Scenario. As long as a piece matches the attribute, historical, and filter selection requirements, it is irrelevant which piece is picked, and so the pieces are picked at random.
  • the system is also capable of dividing the refresh quantity between the streams according to their relative usage so that, for example, if a SoundScape for a client specifies three Streams, two during the first half of the day and one for the last half of the day, and a refresh quantity of 100 pieces is desired, the system prepares for delivery 25 songs from each of the first two Streams and 50 from the third. This ensures that the content refresh is spread evenly throughout the SoundScape's performance. Operation of the Client System
  • the client can begin execution of the performance.
  • the structure of the data held on the client machine is shown in Figure 6. All of the information that is specific to the client in the Master System is downloaded and represented in the Client Piece Library 12 or in the client set of Soundscapes 11 , as shown in Figure 6.
  • This information includes the Zone information in the Zone Table 80, as the system allows one playback device to serve multiple zones.
  • the structure of the Soundscapes data 11 is similar to the structure of the Scenario Database in the Master System shown in Figure 4.
  • the Zone Table 80 describes the different zones in the client's establishment. This is required as a playback device is capable of serving more than one Zone.
  • the Zone Table links to the SoundScape Table 82 which is used to name each SoundScape.
  • the SoundScape Table links to the Daypart Table 84 which specifies which Scenario will play during a given part of the day.
  • the Daypart Table gives both a start and end time for a daypart and no sequence information because a Daypart does not need to be succeeded by or replaced with a different Daypart.
  • the Daypart Table links to the Scenario Table 88 which provides the names of the Scenarios.
  • the Scenario Table links to the Scenario Clock Table 94 which provides the ordering of Streams within a Scenario. This is done using a sequence to determine the playback order.
  • a Stream Contents Table 92 provides a flattened version of the Master Piece Library (as described in relation to Figure 3), in addition to marking which streams a piece belongs to.
  • each piece that was downloaded is associated with a particular Stream in the Stream Contents Table 92.
  • the structure of the Client Piece Library is the same as the structure of the Master Piece Library shown in Figure 3 except that parts of the structure have been flattened. This means that instead of maintaining a relationship between a piece definition and an artist name, the relationship is flattened so that the artist name is moved into the piece definition table as shown in the Stream Contents Table 92. Also, the attribute tree is not sent to the client machine and instead, the joining table is flattened into the piece table in the same way. Because the attribute descriptions are only necessary on the Master System where they are viewed by humans, this flattening does not compromise the operation of the system and means that large amounts of redundant and indeed confidential information is not transmitted to the client. Selection of Pieces Based on Playback Rules
  • the client machine can begin execution of the performance.
  • the client machine (at the correct time) can begin execution of the performance.
  • the client machine (at the correct time) can begin execution of the performance.
  • the client machine (at the correct time) can begin execution of the performance.
  • the following is a description of how pieces are selected for playback.
  • a specific SoundScape is selected from the SoundScape Table 82.
  • This SoundScape may have a number of rules specified in the Rule Table 86. If it does, then these rules are added to the list of rules to apply when selecting a piece.
  • the Scenario provides a specific sequence of Streams from the Scenario Clock Table 94. Based on a current stream indicator, a specific Stream is selected. The Stream may also have a number of rules that are added to the current rule list. All of the unplayed pieces belonging to a specific Stream are then selected.
  • the first available unplayed piece is considered and checked against the Playback Rules. If a piece does not break any rules, it is selected, played and marked as played. If the piece breaks any rules, the piece is discarded and the next available piece is tested against the rules until either one is found and played or all available pieces are exhausted. If all available pieces break at least one rule, then the first piece available is played and marked as played, even though it breaks at least one rule, and the process repeats.
  • An advantage of the method of using playback rules which operate with the detailed list of piece attributes is that any of a very large list of attributes can be used for a rule. For example, because the beginnings and endings of each piece are specified in the list of possible attributes, a rule can be specified that a piece with a certain beginning attribute shall or shall not follow a piece with a certain ending attribute.

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • General Health & Medical Sciences (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

Système expert destiné à fournir aux clients des morceaux audiovisuels sélectionnés dans une grande bibliothèque de morceaux et de sélectionner le moment pour jouer chacun des morceaux. Chaque établissement client est subdivisé en zones, et chaque zone est divisée en des parties de la journée. On identifie les caractéristiques de l'audience cible pour chaque zone et partie de la journée en les sélectionnant dans une longue liste d'attributs possibles (22). Le système expert utilise les attributs sélectionnés pour choisir les morceaux présentant certaines caractéristiques qui seraient adaptées à cette audience cible. Un expert écoute chacun des morceaux placés dans la bibliothèque et confère au morceau plusieurs attributs sélectionnés dans une longue liste d'attributs possibles (23) du morceau. Pour choisir les morceaux qui sont adaptés à un type donné de l'audience cible, un expert crée un spécificateur booléen qui travaille avec les attributs des morceaux pour sélectionner le morceau désiré. (25). L'invention concerne un procédé qui permet de télécharger à un client déterminé les morceaux à sélectionner depuis la bibliothèque, ce qui permet de mettre régulièrement à jour les morceaux avec un nouveau ensemble de morceaux sans dupliquer le contenu. A partir de la bibliothèque du sous-ensemble client, des morceaux sont sélectionnés par l'application d'un ensemble de règles de reproduction qui ont été assemblés à partir de plusieurs niveaux d'entrée d'experts (31). Conformément aux règles de reproduction, les morceaux sont reproduits par l'application d'un ensemble de règles de reproduction qui ont été assemblés à partir de plusieurs niveaux d'entrée d'experts (31). Selon les règles de reproduction, les morceaux sont reproduits dans une séquence qui plaît à l'utilisateur.
PCT/US2001/011106 2000-04-05 2001-04-04 Systeme expert destine a la generation de listes d'ecoute Ceased WO2001077846A1 (fr)

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US7840292B2 (en) 2004-12-10 2010-11-23 Koninklijke Philips Electronics N.V. Multiuser playlist generation

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