A unified view for discriminative objective functions based on negative exponential of difference measure between strings

Atsushi Nakamura*, Erik McDermott, Shinji Watanabe, Shigeru Katagiri

*この研究の対応する著者

研究成果: Conference contribution

12 被引用数 (Scopus)

抄録

This paper presents a novel unified view of a wide variety of objective functions suitable for discriminative training applied to sequential pattern recognition problems, such as automatic speech recognition. Focusing on a central component of conventional objective functions, the sum of modified joint probabilities of observations and strings, the analysis generalizes these objective functions by weighting each term in the sum by an important function, the negative exponential of difference measure between strings. The interesting and valuable results of this investigation are highlighted in a comprehensive relationship chart that covers all of the common approaches (Maximum Mutual Information, Minimum Classification Error, Minimum Phone/Word Error), as well as corresponding novel generalizations and modifications of those approaches.

本文言語English
ホスト出版物のタイトル2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
ページ1633-1636
ページ数4
DOI
出版ステータスPublished - 2009
外部発表はい
イベント2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan, Province of China
継続期間: 2009 4月 192009 4月 24

出版物シリーズ

名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN(印刷版)1520-6149

Conference

Conference2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
国/地域Taiwan, Province of China
CityTaipei
Period09/4/1909/4/24

ASJC Scopus subject areas

  • ソフトウェア
  • 信号処理
  • 電子工学および電気工学

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