Viterbi Approximation of Latent Words Language Models for Automatic Speech Recognition-Reference-Cited by-同舟云学术

Viterbi Approximation of Latent Words Language Models for Automatic Speech Recognition

Published:2019 Issue:0 Volume:27 Page:168-176
ISSN:1882-6652
Container-title:Journal of Information Processing
language:en
Short-container-title:Journal of Information Processing

Author:

Masumura Ryo¹,Asami Taichi¹,Oba Takanobu¹,Masataki Hirokazu¹,Sakauchi Sumitaka¹

Affiliation:

1. NTT Media Intelligence Laboratories, NTT Corporation

Publisher

Information Processing Society of Japan

Subject

General Computer Science

Link

https://www.jstage.jst.go.jp/article/ipsjjip/27/0/27_168/_pdf

Reference37 articles.

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3. [3] Masumura, R., Asami, T., Oba, T., Masataki, H., Sakauchi, S. and Ito, A.: Investigation of Combining Various Major Language Model Technologies including Data Expansion and Adaptation, IEICE Trans. Information and Systems, Vol.E99-D, No.10, pp.2452-2461 (2016).

4. [4] Chen, S.F. and Goodman, J.: An Empirical Study of Smoothing techniques for language modeling, Computer Speech & Language, Vol.13, pp.359-383 (1999).

5. [5] Teh, Y.W.: A Hierarchical Bayesian Language Model based on Pitman-Yor Processes, Proc. Joint Conference of the International Committee on Computational Linguistics and the Association for Computational Linguistics (COLING/ACL), pp.985-992 (2006).

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