Abstract
This paper describes an integrated system to produce a composite recognition output on distant-talking speech when the recognition results from multiple microphone inputs are available. In many cases, the composite recognition result has lower error rate than any other individual output. In this work, the composite recognition result is obtained by applying Bayesian inference. The log likelihood score is assumed to follow a Gaussian distribution, at least approximately. First, the distribution of the likelihood score is estimated in the development set. Then, the confidence interval for the likelihood score is used to remove unreliable microphone channels. Finally, the area under the distribution between the likelihood score of a hypothesis and that of the (N+1)st hypothesis is obtained for every channel and integrated for all channels by Bayesian inference. The proposed system shows considerable performance improvement compared with the result using an ordinary method by the summation of likelihoods as well as any of the recognition results of the channels.
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References
Hughes, T.B., Kim, H., Dibiase, J.H., Silverman, H.F.: Using A Real-Time, Tracking Microphone Array as Input to an HMM Speech Recognize. In: Proc. of ICASSP, vol. 1, pp. 249–252 (1998)
Yamada, T., Makamura, S., Shikano, K.: Hands-free Speech Recognition with Talker Localization by a Microphone Array. Trans. of Information Processing Society of Japan 39(5), 1275–1284 (1998)
Takiguchi, T., Nakamura, S., Shikano, K.: HMM-Seperation Based Speech Recognition for a Distant Moving Speaker. IEEE Trans. on Speech and Audio Processing 9(2), 127–140 (2001)
Yamada, T., Nakamura, S., Shikano, K.: Distant-Talking Speech Recognition Based on a 3-D Viterbi Search Using a Microphone Array. Trans. on Speech and Audio Processing 10(2), 48–56 (2002)
Shimizu, Y., Kajita, S., Takeda, K., Itakura, F.: Speech Recognition Based on Space Diversity Using Distributed Multi-Microphone. In: Proc. of ICASSP, vol. 3, pp. 1747–1750 (2000)
Bolstad, W.M.: Introduction to Bayesian Statistics. John Wiley & Sons, New Jersey (2004)
Neapolitan, R.E.: Learning Bayesian Networks, 2nd edn. Pearson Prentice Hall, Upper Saddle River, New Jersey (2004)
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© 2006 Springer-Verlag Berlin Heidelberg
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Ji, M., Kim, S., Kim, H. (2006). Composite Decision by Bayesian Inference in Distant-Talking Speech Recognition. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2006. Lecture Notes in Computer Science(), vol 4188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11846406_58
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DOI: https://doi.org/10.1007/11846406_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39090-9
Online ISBN: 978-3-540-39091-6
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