音楽音響分析 Instrogram: Probabilistic Representation of Instrument Existence for Polyphonic Music

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Abstract

This paper presents a new technique for recognizing musical instruments in polyphonic music. Since conventional musical instrument recognition in polyphonic music is performed notewise i.e. for each note accurate estimation of the onset time and fundamental frequency (F0) of each note is required. However these estimations are generally not easy in polyphonic music and thus estimation errors severely deteriorated the recognition performance. Without these estimations our technique calculates the temporal trajectory of instrument existence probabilities for every possible F0. The instrument existence probability is defined as the product of a nonspecific instrument existence probability calculated using the PreFEst and a conditional instrument existence probability calculated using hidden Markov models. The instrument existence probability is visualized as a spectrogram-like graphical representation called the instrogram and is applied to MPEG-7 annotation and instrumentation-similaritybased music information retrieval. Experimental results from both synthesized music and real performance recordings have shown that instrograms achieved MPEG-7 annotation (instrument identification) with a precision rate of 87.5% for synthesized music and 69.4% for real performances on average and that the instrumentation similarity measure reflected the actual instrumentation better than an MFCC-based measure.  appendices:<a href="http://www.ipsj.or.jp/08editt/contents/JNL4801/index.html#21"target="_brank">http://www.ipsj.or.jp/08editt/contents/JNL4801/index.html#21</a>This paper presents a new technique for recognizing musical instruments in polyphonic music. Since conventional musical instrument recognition in polyphonic music is performed notewise, i.e., for each note, accurate estimation of the onset time and fundamental frequency (F0) of each note is required. However, these estimations are generally not easy in polyphonic music, and thus estimation errors severely deteriorated the recognition performance. Without these estimations, our technique calculates the temporal trajectory of instrument existence probabilities for every possible F0. The instrument existence probability is defined as the product of a nonspecific instrument existence probability calculated using the PreFEst and a conditional instrument existence probability calculated using hidden Markov models. The instrument existence probability is visualized as a spectrogram-like graphical representation called the instrogram and is applied to MPEG-7 annotation and instrumentation-similaritybased music information retrieval. Experimental results from both synthesized music and real performance recordings have shown that instrograms achieved MPEG-7 annotation (instrument identification) with a precision rate of 87.5% for synthesized music and 69.4% for real performances on average and that the instrumentation similarity measure reflected the actual instrumentation better than an MFCC-based measure.appendices:<a href="http://www.ipsj.or.jp/08editt/contents/JNL4801/index.html#21"target="_brank">http://www.ipsj.or.jp/08editt/contents/JNL4801/index.html#21</a>

This paper presents a new technique for recognizing musical instruments in polyphonic music. Since conventional musical instrument recognition in polyphonic music is performed notewise, i.e., for each note, accurate estimation of the onset time and fundamental frequency (FO) of each note is required. However, these estimations are generally not easy in polyphonic music, and thus estimation errors severely deteriorated the recognition performance. Without these estimations, our technique calculates the temporal trajectory of instrument existence probabilities for every possible FO. The instrument existence probability is denned as the product of a nonspecific instrument existence probability calculated using the PreFEst and a conditional instrument existence probability calculated using hidden Markov models. The instrument existence probability is visualized as a spectrogram-like graphical representation called the instrogram and is applied to MPEG-7 annotation and instrumentation-similarity-based music information retrieval. Experimental results from both synthesized music and real performance recordings have shown that instrograms achieved MPEG-7 annotation (instrument identification) with a precision rate of 87.5% for synthesized music and 69.4% for real performances on average and that the instrumentation similarity measure reflected the actual instrumentation better than an MFCC-based measure.

Journal

  • IPSJ journal

    IPSJ journal 48(1), 214-226, 2007-01-15

    Information Processing Society of Japan (IPSJ)

References:  20

Cited by:  4

Codes

  • NII Article ID (NAID)
    110006152198
  • NII NACSIS-CAT ID (NCID)
    AN00116647
  • Text Lang
    ENG
  • Article Type
    Journal Article
  • ISSN
    1882-7764
  • NDL Article ID
    8649884
  • NDL Source Classification
    ZM13(科学技術--科学技術一般--データ処理・計算機)
  • NDL Call No.
    Z14-741
  • Data Source
    CJP  CJPref  NDL  NII-ELS  IPSJ 
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