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

Atsushi Nakamura; Erik McDermott; Shinji Watanabe; Shigeru Katagiri

doi:10.1109/ICASSP.2009.4959913

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

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
Pages	1633-1636
Number of pages	4
DOIs	https://doi.org/10.1109/ICASSP.2009.4959913
Publication status	Published - 2009
Externally published	Yes
Event	2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan, Province of China Duration: 2009 Apr 19 → 2009 Apr 24

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)	1520-6149

Conference

Conference	2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
Country/Territory	Taiwan, Province of China
City	Taipei
Period	09/4/19 → 09/4/24

Keywords

Automatic speech recognition
Discriminative training
Generalized objective function
Laplace-Stieltjes transform
Negative exponential function

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

Access to Document

10.1109/ICASSP.2009.4959913

Cite this

Nakamura, A., McDermott, E., Watanabe, S., & Katagiri, S. (2009). A unified view for discriminative objective functions based on negative exponential of difference measure between strings. In 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009 (pp. 1633-1636). [4959913] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2009.4959913

A unified view for discriminative objective functions based on negative exponential of difference measure between strings. / Nakamura, Atsushi; McDermott, Erik; Watanabe, Shinji et al.

2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009. 2009. p. 1633-1636 4959913 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Nakamura, A, McDermott, E, Watanabe, S & Katagiri, S 2009, A unified view for discriminative objective functions based on negative exponential of difference measure between strings. in 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009., 4959913, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 1633-1636, 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009, Taipei, Taiwan, Province of China, 09/4/19. https://doi.org/10.1109/ICASSP.2009.4959913

Nakamura A, McDermott E, Watanabe S, Katagiri S. A unified view for discriminative objective functions based on negative exponential of difference measure between strings. In 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009. 2009. p. 1633-1636. 4959913. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP.2009.4959913

Nakamura, Atsushi ; McDermott, Erik ; Watanabe, Shinji et al. / A unified view for discriminative objective functions based on negative exponential of difference measure between strings. 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009. 2009. pp. 1633-1636 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

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abstract = "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.",

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AB - 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.

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

Abstract

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Keywords

ASJC Scopus subject areas

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