Automatic Musical Genre Classification of Audio Signals

By George Tzanetakis. International Society for Music Information Retrieval Conference, 2001

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Learning Features from Music Audio with Deep Belief Networks (2010, methodology): “The dataset was introduced in [24], and have since been used as a reference for the genre recognition task.”
Musical genre classification of audio signals (2002, background): “Reference [17] contains some early work and preliminary results in automatic musical genre classification.”
Content-based organization and visualization of music archives (2002, background): “A more practical approach to the topic was presented in [31] where music given as raw audio is automatically classified into genres based on musical surface and rhythm features.”
Content-Based Music Information Retrieval: Current Directions and Future Challenges (2008, methodology): “For example, Tzanetakis et al. [ 95 ] developed the BGenreSpace[ interface for browsing music collections in a threedimensional space into which musical pieces are projected according to their similarity.”
Features for audio and music classification (2003, result): “In comparison to results of other studies of music genre classification (Tzanetakis et al., 2001; Tzanetakis & Cook, 2002), our features looks quite promising.”
Music Similarity Measures: What's the use? (2002, background): “Among related work in this domain, Automatic Genre Classification ([5]) tries to categorize music titles into genre classes by looking at spectral or temporal signal features.”