Presentation | 2006/12/14 Minimum Bayes-Risk Decoding using Wordgraph and Key-sentence Extraction Hiroaki NANJO, Tatsuya KAWAHARA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Speech recognition strategy for open-domain speech understanding and its application to a key-sentence extraction, which is a first step of speech understanding, are presented. Firstly, a weighted word error rate (WWER), which is an evaluation measure giving a weight on errors from a viewpoint of speech understanding, is described. Then, we show a decoding method to minimize WWER based on Minimum Bayes-Risk (MBR) framework. We have investigated N-best list based MBR decoding. In this paper, several wordgraph based MBR decoding algorithms are presented, and then, we show the effectiveness of confusion network based decoding strategy. Finally, we demonstrate that the decoding method works reasonably for improving both WWER and key sentence indexing. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | speech recognition / speech understanding / Minimum Bayes-Risk decoding key sentence extraction / wordgraph |
Paper # | NLC2006-50,SP2006-106 |
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Committee | SP |
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Conference Date | 2006/12/14(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (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) | Minimum Bayes-Risk Decoding using Wordgraph and Key-sentence Extraction |
Sub Title (in English) | |
Keyword(1) | speech recognition |
Keyword(2) | speech understanding |
Keyword(3) | Minimum Bayes-Risk decoding key sentence extraction |
Keyword(4) | wordgraph |
1st Author's Name | Hiroaki NANJO |
1st Author's Affiliation | Faculty of Science and Technology, Ryukoku University() |
2nd Author's Name | Tatsuya KAWAHARA |
2nd Author's Affiliation | Graduate School of Informatics, Kyoto University |
Date | 2006/12/14 |
Paper # | NLC2006-50,SP2006-106 |
Volume (vol) | vol.106 |
Number (no) | 443 |
Page | pp.pp.- |
#Pages | 6 |
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