Automatic Musical Genre Classification Of Audio Signals

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Automatic Musical Genre Classification Of Audio Signals (2002)

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by George Tzanetakis , Georg Essl , Perry Cook

Venue:	IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING
Citations:	810 - 32 self

BibTeX

@INPROCEEDINGS{Tzanetakis02automaticmusical,
    author = {George Tzanetakis and Georg Essl and Perry Cook},
    title = {Automatic Musical Genre Classification Of Audio Signals},
    booktitle = {IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING},
    year = {2002},
    pages = {293--302},
    publisher = {}
}

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Abstract

... describe music. They are commonly used to structure the increasing amounts of music available in digital form on the Web and are important for music information retrieval. Genre categorization for audio has traditionally been performed manually. A particular musical genre is characterized by statistical properties related to the instrumentation, rhythmic structure and form of its members. In this work, algorithms for the automatic genre categorization of audio signals are described. More specifically, we propose a set of features for representing texture and instrumentation. In addition a novel set of features for representing rhythmic structure and strength is proposed. The performance of those feature sets has been evaluated by training statistical pattern recognition classifiers using real world audio collections. Based on the automatic hierarchical genre classification two graphical user interfaces for browsing and interacting with large audio collections have been developed.

Keyphrases

audio signal automatic musical genre classification rhythmic structure music information retrieval particular musical genre novel set feature set automatic genre categorization describe music statistical pattern recognition classifier automatic hierarchical genre classification digital form real world audio collection graphical user interface genre categorization statistical property large audio collection

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