Automatic Drum Sound Description for Real-World Music Using Template Adaptation and Matching Methods

نویسندگان

  • Kazuyoshi Yoshii
  • Masataka Goto
  • Hiroshi G. Okuno
چکیده

This paper presents an automatic description system of drum sounds for real-world musical audio signals. Our system can represent onset times and names of drums by means of drum descriptors defined in the context of MPEG-7. For their automatic description, drum sounds must be identified in such polyphonic signals. The problem is that acoustic features of drum sounds vary with each musical piece and precise templates for them cannot be prepared in advance. To solve this problem, we propose new template-adaptation and template-matching methods. The former method adapts a single seed template prepared for each kind of drums to the corresponding drum sound appearing in an actual musical piece. The latter method then can detect all the onsets of each drum by using the corresponding adapted template. The onsets of bass and snare drums in any piece can thus be identified. Experimental results showed that the accuracy of identifying bass and snare drums in popular music was about 90%. Finally, we define drum descriptors in the MPEG-7 format and demonstrate an example of the automatic drum sound description for a piece of popular music. keywords: automatic description, polyphonic music, drum sounds, template-adaptation, template-matching

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تاریخ انتشار 2004