Presentation 2010-01-21
Online speaker clustering using an ergodic HMM and its application to meeting minute generation
Takafumi KOSHINAKA, Kentaro NAGATOMO, Kenji SATOH,
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Abstract(in English) A novel online speaker clustering method suitable for real-time applications is proposed. Using an ergodic hidden Markov model (HMM), it employs incremental learning based on a variational Bayesian framework and provides probabilistic (non-deterministic) decisions for each input utterance, directly considering the specific history of preceding utterances. It makes possible more robust cluster estimation and precise classification of utterances than do conventional online methods. Experiments on meeting-speech data show that the proposed method produces 60-80% fewer classification errors than a conventional method does. They also show that it reduces speech recognition errors when combined with unsupervised speaker adaptation.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Hidden Markov models / variational Bayesian inference / model selection / meeting speech recognition
Paper # CQ2009-62,PRMU2009-161,SP2009-102,MVE2009-84
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Conference Information
Committee CQ
Conference Date 2010/1/14(1days)
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Paper Information
Registration To Communication Quality (CQ)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Online speaker clustering using an ergodic HMM and its application to meeting minute generation
Sub Title (in English)
Keyword(1) Hidden Markov models
Keyword(2) variational Bayesian inference
Keyword(3) model selection
Keyword(4) meeting speech recognition
1st Author's Name Takafumi KOSHINAKA
1st Author's Affiliation Common Platform Software Res. Labs., NEC Corporation()
2nd Author's Name Kentaro NAGATOMO
2nd Author's Affiliation Common Platform Software Res. Labs., NEC Corporation
3rd Author's Name Kenji SATOH
3rd Author's Affiliation Common Platform Software Res. Labs., NEC Corporation
Date 2010-01-21
Paper # CQ2009-62,PRMU2009-161,SP2009-102,MVE2009-84
Volume (vol) vol.109
Number (no) 373
Page pp.pp.-
#Pages 6
Date of Issue