Speaker clustering based on utterance-oriented Dirichlet process mixture model

Naohiro Tawara*, Shinji Watanabe, Tetsuji Ogawa, Tetsunori Kobayashi

*この研究の対応する著者

研究成果: Conference article査読

5 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)2905-2908
ページ数4
ジャーナルProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
出版ステータスPublished - 2011 12月 1
イベント12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy
継続期間: 2011 8月 272011 8月 31

ASJC Scopus subject areas

  • 言語および言語学
  • 人間とコンピュータの相互作用
  • 信号処理
  • ソフトウェア
  • モデリングとシミュレーション

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