Genre Classification using Harmony Rules Induced from Automatic Chord Transcriptions

TitleGenre Classification using Harmony Rules Induced from Automatic Chord Transcriptions
Publication TypeConference Paper
Year of Publication2009
Conference NameInternational Society for Music Information Retrieval Conference
AuthorsAnglade, A., Ramirez R., & Dixon S.
AbstractWe present an automatic genre classification technique making use of frequent chord sequences that can be applied on symbolic as well as audio data. We adopt a first-order logic representation of harmony and musical genres: pieces of music are represented as lists of chords and musical genres are seen as context-free definite clause grammars using subsequences of these chord lists. To induce the contextfree definite clause grammars characterising the genres we use a first-order logic decision tree induction algorithm. We report on the adaptation of this classification framework to audio data using an automatic chord transcription algorithm. We also introduce a high-level harmony representation scheme which describes the chords in term of both their degrees and chord categories. When compared to another high-level harmony representation scheme used in a previous study, it obtains better classification accuracies and shorter run times. We test this framework on 856 audio files synthesized from Band in a Box files and covering 3 main genres, and 9 subgenres. We perform 3-way and 2-way classification tasks on these audio files and obtain good classification results: between 67% and 79% accuracy for the 2-way classification tasks and between 58% and 72% accuracy for the 3-way classification tasks.