Speech corpus recycling for acoustic cross-domain environments for automatic speech recognition
Author:
Affiliation:
1. IBM Research
2. IBM Research, T.J. Watson Research Center
3. Nuance Communications Inc.
Publisher
Acoustical Society of Japan
Subject
Acoustics and Ultrasonics
Link
https://www.jstage.jst.go.jp/article/ast/37/2/37_E1501/_pdf
Reference29 articles.
1. 1) M. J. F. Gales and S. J. Young, ``Robust continuous speech recognition using parallel model combination,'' IEEE Trans. Speech Audio Process., 4, 352-359 (1996).
2. 2) P. J. Moreno, B. Raj and R. M. Stern, ``A vector Taylor series approach for environment-independent speech recognition,'' Proc. Int. Conf. Acoust. Speech Signal Process., Vol. 2, pp. 733-736 (1996).
3. 3) M. J. F. Gales, ``Maximum likelihood linear transformations for HMM-based speech recognition,'' Comput. Speech Lang., 12, 75-98 (1998).
4. 4) J. L. Gauvain and C. H. Lee, ``Maximum a posteriori estimation for multivariate Gaussian mixture observations of Markov chains,'' IEEE Trans. Speech Audio Process., 2, 291-298 (1994).
5. 5) D. Povey, B. Kingsbury, L. Mangu, G. Saon, H. Soltau and G. Zweig, ``fMPE: Discriminatively trained features for speech recognition,'' Proc. Int. Conf. Acoust. Speech Signal Process., pp. 961-964 (2005).
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