[go: up one dir, main page]

Langlois et al., 2009 - Google Patents

A Music Classification Method based on Timbral Features.

Langlois et al., 2009

View PDF
Document ID
7682896480864797359
Author
Langlois T
Marques G
Publication year
Publication venue
ISMIR

External Links

Snippet

This paper describes a method for music classification based solely on the audio contents of the music signal. More specifically, the audio signal is converted into a compact symbolic representation that retains timbral characteristics and accounts for the temporal structure of a …
Continue reading at citeseerx.ist.psu.edu (PDF) (other versions)

Classifications

    • 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
    • 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
    • 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
    • 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
    • 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
    • G06F17/30749—Audio data retrieval using information manually generated or using information not derived from the audio data, e.g. title and artist information, time and location information, usage information, user ratings
    • 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
    • G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
    • G10L15/065—Adaptation
    • G10L15/07—Adaptation to the speaker
    • 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
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H2240/00—Data organisation or data communication aspects, specifically adapted for electrophonic musical tools or instruments
    • G10H2240/075—Musical metadata derived from musical analysis or for use in electrophonic musical instruments
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H1/00—Details of electrophonic musical instruments
    • G10H1/36—Accompaniment arrangements
    • 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
    • G10L17/26—Recognition of special voice characteristics, e.g. for use in lie detectors; Recognition of animal voices
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H2250/00—Aspects of algorithms or signal processing methods without intrinsic musical character, yet specifically adapted for or used in electrophonic musical processing
    • G10H2250/131—Mathematical functions for musical analysis, processing, synthesis or composition
    • G10H2250/215—Transforms, i.e. mathematical transforms into domains appropriate for musical signal processing, coding or compression
    • G10H2250/235—Fourier transform; Discrete Fourier Transform [DFT]; Fast Fourier Transform [FFT]
    • 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
    • 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

Similar Documents

Publication Publication Date Title
Cataltepe et al. Music genre classification using MIDI and audio features
Murthy et al. Content-based music information retrieval (cb-mir) and its applications toward the music industry: A review
Shao et al. Unsupervised classification of music genre using hidden markov model
Zhang Automatic singer identification
Jiang et al. Music type classification by spectral contrast feature
Tsai et al. Automatic singer recognition of popular music recordings via estimation and modeling of solo vocal signals
CN100397387C (en) Abstract production method and device for digital sound data
Birmingham et al. MUSART: Music Retrieval Via Aural Queries.
Liu et al. A study on content-based classification and retrieval of audio database
US20100198760A1 (en) Apparatus and methods for music signal analysis
Langlois et al. A Music Classification Method based on Timbral Features.
Schuller et al. Determination of nonprototypical valence and arousal in popular music: features and performances
Turnbull et al. Modelling music and words using a multi-class naıve bayes approach
Zhang et al. System and method for automatic singer identification
Liu et al. Content-based audio classification and retrieval using a fuzzy logic system: towards multimedia search engines
Nagavi et al. Overview of automatic Indian music information recognition, classification and retrieval systems
Fuhrmann et al. Scalability, Generality and Temporal Aspects in Automatic Recognition of Predominant Musical Instruments in Polyphonic Music.
Zhu et al. Musical genre classification by instrumental features
West Novel techniques for audio music classification and search
Qin et al. A bag-of-tones model with MFCC features for musical genre classification
West et al. Incorporating machine-learning into music similarity estimation
Reed et al. On the importance of modeling temporal information in music tag annotation
Dash et al. A Comprehensive Review on Audio based Musical Instrument Recognition: Human-Machine Interaction towards Industry 4.0
Shen et al. Effective music tagging through advanced statistical modeling
Kroher The flamenco cante: Automatic characterization of flamenco singing by analyzing audio recordings