Presentation | 1997/2/21 Note recognition using the statistical information about note transition Tomoyoshi Kinoshita, Hideya Muraoka, Hidehiko Tanaka, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Previously, we have proposed a processing model OPTIMA for music scene analysis, and implemented its experimental system. However, its recognition accuracy was not practical. The OPTIMA processing architecture is the framework where multiple sources of information are integrated. Due to this feature, we can improve its accuracy by adding new processing modules. The objective of this paper is improvement of recognition accuracy using statistics of note transition. In this paper, first we analyze the transition of notes and construct a knowledge source for OPTIMA. We then propose a novel process which gives probabilistic information about note ptransition. Experimental results show the effectiveness of this process. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Music scene analysis / Note transition / Auditory scene analysis / Probabilistic information integration |
Paper # | SP96-116 |
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Committee | SP |
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Conference Date | 1997/2/21(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Speech (SP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Note recognition using the statistical information about note transition |
Sub Title (in English) | |
Keyword(1) | Music scene analysis |
Keyword(2) | Note transition |
Keyword(3) | Auditory scene analysis |
Keyword(4) | Probabilistic information integration |
1st Author's Name | Tomoyoshi Kinoshita |
1st Author's Affiliation | University of Tokyo() |
2nd Author's Name | Hideya Muraoka |
2nd Author's Affiliation | University of Tokyo |
3rd Author's Name | Hidehiko Tanaka |
3rd Author's Affiliation | University of Tokyo |
Date | 1997/2/21 |
Paper # | SP96-116 |
Volume (vol) | vol.96 |
Number (no) | 540 |
Page | pp.pp.- |
#Pages | 6 |
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