Presentation 2011-12-19
Speaker Clustering Using Speaker Subspace Obtained Dynamically Based on Variance of Intra-Utterance
Yuki ISHIKAWA, Masafumi NISHIDA, Seiichi YAMAMOTO,
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Abstract(in English) Speech has two types of information, such as phoneme and speaker. If these information are separated, robust speaker clustering can be achieved. It is necessary to suppress the phonetic information for each utterance because variance of utterance duration is large in multi-party conversation. We propose a speaker clustering method using Gaussian mixture model in flexibly selected speaker subspace based on variance of intra-utterance. We carried out speaker clustering experiments compared with conventional methods based on Bayesian information criterion and Gaussian mixture model in an observation space. The experimental results showed that the proposed method can achieve higher clustering accuracy than conventional methods.
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Keyword(in English) speaker clustering / variance of intra-utterance / speaker subspace / Gaussian mixture model / principal component analysis
Paper # NLC2011-42,SP2011-87
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Committee NLC
Conference Date 2011/12/12(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Speaker Clustering Using Speaker Subspace Obtained Dynamically Based on Variance of Intra-Utterance
Sub Title (in English)
Keyword(1) speaker clustering
Keyword(2) variance of intra-utterance
Keyword(3) speaker subspace
Keyword(4) Gaussian mixture model
Keyword(5) principal component analysis
1st Author's Name Yuki ISHIKAWA
1st Author's Affiliation Graduate School of Engineering, Doshisha University()
2nd Author's Name Masafumi NISHIDA
2nd Author's Affiliation Graduate School of Engineering, Doshisha University
3rd Author's Name Seiichi YAMAMOTO
3rd Author's Affiliation Graduate School of Engineering, Doshisha University
Date 2011-12-19
Paper # NLC2011-42,SP2011-87
Volume (vol) vol.111
Number (no) 364
Page pp.pp.-
#Pages 5
Date of Issue