TY - JOUR
T1 - Speaker clustering based on utterance-oriented Dirichlet process mixture model
AU - Tawara, Naohiro
AU - Watanabe, Shinji
AU - Ogawa, Tetsuji
AU - Kobayashi, Tetsunori
PY - 2011
Y1 - 2011
N2 - This paper provides the analytical solution and algorithm of UO-DPMM based on a non-parametric Bayesian manner, and thus realizes fully Bayesian speaker clustering. We carried out preliminary speaker clustering experiments by using a TIMIT database to compare the proposed method with the conventional Bayesian Information Criterion (BIC) based method, which is an approximate Bayesian approach. The results showed that the proposed method outperformed the conventional one in terms of both computational cost and robustness to changes in tuning parameters.
AB - This paper provides the analytical solution and algorithm of UO-DPMM based on a non-parametric Bayesian manner, and thus realizes fully Bayesian speaker clustering. We carried out preliminary speaker clustering experiments by using a TIMIT database to compare the proposed method with the conventional Bayesian Information Criterion (BIC) based method, which is an approximate Bayesian approach. The results showed that the proposed method outperformed the conventional one in terms of both computational cost and robustness to changes in tuning parameters.
KW - Gibbs sampling
KW - Non-parametric Bayesian model
KW - Speaker clustering
KW - Utterance-oriented DPMM
UR - http://www.scopus.com/inward/record.url?scp=84865792512&partnerID=8YFLogxK
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M3 - Conference article
AN - SCOPUS:84865792512
SN - 2308-457X
SP - 2905
EP - 2908
JO - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
JF - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
T2 - 12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011
Y2 - 27 August 2011 through 31 August 2011
ER -