Abstract
Recent advances in Hidden Markov Model (HMM) based speaker-independent connected digit recognition have usually tended to make the models more complex. This paper concentrates on improving the training techniques in order to make the most of the available parameters. A new algorithm, Corrective MMI Training is introduced. Use of this algorithm resulted in significant improvements in our recognition rates. We now obtain less than 2% string error rate using semi-continuous HMMs with two models per digit.
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References
G.R. Doddington, Phonetically Sensitive Discriminants for Improved Speech Recognition, ICASSP-89, paper S10b.11
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© 1992 Springer-Verlag Berlin Heidelberg
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Normandin, Y., Cardin, R. (1992). Developments in High-Performance Connected Digit Recognition. In: Laface, P., De Mori, R. (eds) Speech Recognition and Understanding. NATO ASI Series, vol 75. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76626-8_8
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DOI: https://doi.org/10.1007/978-3-642-76626-8_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-76628-2
Online ISBN: 978-3-642-76626-8
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