[go: up one dir, main page]

Tang et al., 2021 - Google Patents

Harmonic classification with enhancing music using deep learning techniques

Tang et al., 2021

View PDF @Full View
Document ID
15385668036828142310
Author
Tang W
Gu L
Publication year
Publication venue
Complexity

External Links

Snippet

Automatic extraction of features from harmonic information of music audio is considered in this paper. Automatically obtaining of relevant information is necessary not just for analysis but also for the commercial issue such as music program of tutoring and generating of lead …
Continue reading at onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3074—Audio data retrieval
    • G06F17/30743—Audio data retrieval using features automatically derived from the audio content, e.g. descriptors, fingerprints, signatures, MEP-cepstral coefficients, musical score, tempo
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3074—Audio data retrieval
    • G06F17/30755—Query formulation specially adapted for audio data retrieval
    • G06F17/30758—Query by example, e.g. query by humming
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H2210/00—Aspects or methods of musical processing having intrinsic musical character, i.e. involving musical theory or musical parameters or relying on musical knowledge, as applied in electrophonic musical tools or instruments
    • G10H2210/031—Musical analysis, i.e. isolation, extraction or identification of musical elements or musical parameters from a raw acoustic signal or from an encoded audio signal
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/08—Speech classification or search
    • G10L15/18—Speech classification or search using natural language modelling
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H1/00—Details of electrophonic musical instruments
    • G10H1/36—Accompaniment arrangements
    • G10H1/38—Chord
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H1/00—Details of electrophonic musical instruments
    • G10H1/0008—Associated control or indicating means
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/90—Pitch determination of speech signals
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use
    • G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use for comparison or discrimination
    • G10L25/66—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use for comparison or discrimination for extracting parameters related to health condition
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L17/00—Speaker identification or verification
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signal, using source filter models or psychoacoustic analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H2240/00—Data organisation or data communication aspects, specifically adapted for electrophonic musical tools or instruments
    • G10H2240/121—Musical libraries, i.e. musical databases indexed by musical parameters, wavetables, indexing schemes using musical parameters, musical rule bases or knowledge bases, e.g. for automatic composing methods
    • G10H2240/131—Library retrieval, i.e. searching a database or selecting a specific musical piece, segment, pattern, rule or parameter set
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/003—Changing voice quality, e.g. pitch or formants
    • G10L21/007—Changing voice quality, e.g. pitch or formants characterised by the process used
    • G10L21/013—Adapting to target pitch

Similar Documents

Publication Publication Date Title
Benetos et al. Automatic music transcription: An overview
Bretan et al. A unit selection methodology for music generation using deep neural networks
Benetos et al. Automatic music transcription: challenges and future directions
Kolozali et al. Automatic ontology generation for musical instruments based on audio analysis
Liebman et al. Artificial musical intelligence: A survey
Nuttall et al. The matrix profile for motif discovery in audio-an example application in carnatic music
Anglade et al. Improving music genre classification using automatically induced harmony rules
Lerch Audio content analysis
Tang et al. Harmonic classification with enhancing music using deep learning techniques
Rajan et al. Multi-channel CNN-Based Rāga Recognition in Carnatic Music Using Sequential Aggregation Strategy
Yeh et al. Popular music representation: chorus detection & emotion recognition
Yang et al. Highlighting root notes in chord recognition using cepstral features and multi-task learning
Sun et al. Music informer as an efficient model for music generation
Zhang Music data feature analysis and extraction algorithm based on music melody contour
Chakrabarty et al. A foremost survey on state-of-the-art computational music research
Wu et al. Construction and Application of a Piano Playing Pitch Recognition Model Based on Neural Network
Shirude et al. Recognizing raga of indian classical songs using regular expressions
Lei Multiple Musical Instrument Signal Recognition Based on Convolutional Neural Network
Kolozali et al. A framework for automatic ontology generation based on semantic audio analysis
Kum et al. Classification-based singing melody extraction using Deep Convolutional Neural Networks
Mo et al. [Retracted] Analysis of Computer Visualized Sound Parameters of Vocal Music Singing Based on Deep Learning
Rege et al. Audio Classification for Melody Transcription in the Context of Indian Art Music
Bai [Retracted] Improvement of Speech Recognition Technology in Piano Music Scene Based on Deep Learning of Internet of Things
Patakis et al. Semantic-Aware Interpretable Multimodal Music Auto-Tagging
Crayencour et al. Learning, probability and logic: Toward a unified approach for content-based music information retrieval