Improving Music Genre Classification by Short Time Feature Integration

Publication: ResearchPoster – Annual report year: 2005


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Many different short-time features (derived from 10-30ms of audio) have been proposed for music segmentation, retrieval and genre classification. Often the available time frame of the music to make a decision (the decision time horizon) is in the range of seconds instead of milliseconds. The problem of making new features on the larger time scale from the short-time features (feature integration) has only received little attention. This paper investigates different methods for feature integration (early information fusion) and late information fusion (assembling of probabilistic outputs or decisions from the classifier, e.g. majority voting) for music genre classification.
Original languageEnglish
Publication date2005
StatePublished - 2005
EventIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2005) - Philadelphia, Pennsylvania, United States


ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2005)
CountryUnited States
CityPhiladelphia, Pennsylvania
Period23/03/2005 → …


  • Information Fusion, Music genre, Autoregressive Model
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ID: 2871617