TR2004-078

Independent Component Analysis for Automatic Note Extraction from Musical Trills


    •  Brown, J.C., Smaragdis, P., "Independent Component Analysis for Automatic Note Extraction from Musical Trills", Journal of the Acoustical Society of America, Vol. 115, No. 5, pp. 1851-2634, May 2004.
      BibTeX TR2004-078 PDF
      • @article{Brown2004may,
      • author = {Brown, J.C. and Smaragdis, P.},
      • title = {Independent Component Analysis for Automatic Note Extraction from Musical Trills},
      • journal = {Journal of the Acoustical Society of America},
      • year = 2004,
      • volume = 115,
      • number = 5,
      • pages = {1851--2634},
      • month = may,
      • url = {https://www.merl.com/publications/TR2004-078}
      • }
  • Research Areas:

    Artificial Intelligence, Speech & Audio

Abstract:

The method of principal component analysis, which is based on second-order statistics (or linear independence), has long been used for redundancy reduction of audio data. The more recent technique of independent component analysis, enforcing much stricture statistical criteria based on higher-order statistical independence, is introduced and shown to be far superior in separating independent musical sources. This theory has been applied to piano trills and a databse of trill rates was assembled from experiments with a computer-driven piano, recordings of a professional pianist, and commercially available compact disks. The method of independent component analysis has thus been shown to be an outstanding, effiective means of automatically extracting interesting musical information from a sea of redundant data.

 

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