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Musical genre classification of audio signals - Speech and ...

    http://dspace.library.uvic.ca:8080/bitstream/handle/1828/1344/tsap02gtzan.pdf?sequence=1
    Musical Genre Classification of Audio Signals George Tzanetakis, Student Member, IEEE, and Perry Cook, Member, IEEE Abstract— Musical genres are categorical labels created by hu-mans to characterize pieces of music. A musical genre is char-acterized by the common characteristics shared by its members.

(PDF) Musical genre classification of audio signals ...

    https://www.academia.edu/889941/Musical_genre_classification_of_audio_signals
    TZANETAKIS AND COOK: MUSICAL GENRE CLASSIFICATION OF AUDIO SIGNALS 295 3) Spectral Flux: The spectral flux is defined as the squared 7) Low-Energy Feature: Low energy is the only feature that difference between the normalized magnitudes of successive is based on the texture window rather than the analysis window. spectral distributions It is defined as the …

(PDF) Musical Genre Classification of Audio Signals

    https://www.researchgate.net/publication/3333877_Musical_Genre_Classification_of_Audio_Signals
    In this paper, the automatic classification of audio signals into an hierarchy of musical genres is explored. More specifically, three feature sets for representing timbral texture, rhythmic ...

[PDF] Musical genre classification of audio signals ...

    https://www.semanticscholar.org/paper/Musical-genre-classification-of-audio-signals-Tzanetakis-Cook/7ab881283270e427b05c6e9469562ff39dd6282a
    The automatic classification of audio signals into an hierarchy of musical genres is explored and three feature sets for representing timbral texture, rhythmic content and pitch content are proposed. Musical genres are categorical labels created by humans to characterize pieces of music.

Automatic Musical Genre Classification Of Audio Signals

    https://www.cs.princeton.edu/sound/publications/2001_ismir_amgc.pdf
    addition to the development of audio information retrieval systems for music. In this work, algorithms for automatic genre classification are explored. A set of features for representing the music surface and rhythmic structure of audio signals is proposed. The performance of this feature set is evaluated by training statistical pattern recognition classifiers using audio …

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