Presentation 2000/6/15
SP2000-11 Selective training of speaker-clustered HMMs
Shoei SATO, Hiroyuki SEGI, Kazuo ONOE, Toru IMAI, Hideki TANAKA, Akio ANDO,
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Abstract(in English) This paper proposes a method of constructing acoustic models for automatic news subtitling. In this method, two-stage clustering is used for an adaptation-data selection from a large-scale database. The first stage generates GMMs from a small amount of data and second atage clusters a large-scale database by the GMMs. A broadcast news transcription experiment showed that the proposed method reduced in toth a word error rate and processing time. The best result in the experiment showed 33% WER reduction and 25% decoding time reduction compared with the baseline method, which had no clustering. Furthermore, we found that it takes just 0.4 seconds from the beginning of an input utterance to select an HMM correctly. The result showed 18% processing time reduction in total compared with the baseline method.
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Keyword(in English) Broadcast news / subtitling / speech recognition / acoustic model / HMM / clustering / GMM
Paper # SP2000-11
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Committee SP
Conference Date 2000/6/15(1days)
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Paper Information
Registration To Speech (SP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) SP2000-11 Selective training of speaker-clustered HMMs
Sub Title (in English)
Keyword(1) Broadcast news
Keyword(2) subtitling
Keyword(3) speech recognition
Keyword(4) acoustic model
Keyword(5) HMM
Keyword(6) clustering
Keyword(7) GMM
1st Author's Name Shoei SATO
1st Author's Affiliation NHK Science & Technical Research Laboratories()
2nd Author's Name Hiroyuki SEGI
2nd Author's Affiliation NHK Science & Technical Research Laboratories
3rd Author's Name Kazuo ONOE
3rd Author's Affiliation NHK Science & Technical Research Laboratories
4th Author's Name Toru IMAI
4th Author's Affiliation NHK Science & Technical Research Laboratories
5th Author's Name Hideki TANAKA
5th Author's Affiliation NHK Science & Technical Research Laboratories
6th Author's Name Akio ANDO
6th Author's Affiliation NHK Science & Technical Research Laboratories
Date 2000/6/15
Paper # SP2000-11
Volume (vol) vol.100
Number (no) 136
Page pp.pp.-
#Pages 7
Date of Issue