Music scene description

Signal Processing Methods for Music Transcription

Volumn , Issue , 2006, Pages 327-359

  Goto, Masataka ^a  

^a NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

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EID: 77949637898     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/0-387-32845-9_11     Document Type: Chapter

References (9)

1. The term 'automatic music transcription' in this chapter refers to a traditional approach of transcribing all musical notes as a score, while the term 'automatic music transcription' in this book has a broader meaning including the music scene description as described in Chapter 1 of this volume.
2. The method finds the FO whose harmonics are most predominant in those limited frequency ranges. In other words, whether the FO is within each limited range or not, PreFEst tries to estimate the FO which is supported by predominant harmonic frequency components within that range.
3. In implementing the PreFEst core, this iterative computation is simple enough to perform only (11.25), (11.26), (11.27), and (11.28).
4. Masataka Goto's survey of Japan's popular music hit chart (top 20 singles ranked weekly from 2000 to 2003) showed that modulation occurred in chorus repetitions in 152 songs (10.3%) out of 1481.
5. The window length is determined to obtain good frequency resolution in a lowfrequency region.
6. As described in Section 4.6, p. 112, the similarity matrix can also be used to examine rhythmic structure.
7. all (t, l) is evaluated along with the real-time audio input for a real-time system based on RefraiD. On the other hand, it is evaluated at the end of a song for a nonreal-time off-line analysis.
8. all(t, l) therefore simply one dimensional along l.
9. all(t, l), the higher the summation result by (11.34).