Efficient speech recognition using subvector quantization and discrete-mixture HMMs

This paper introduces a new form of observation distributions for hidden Markov models (HMMs), combining subvector quantization and mixtures of discrete distributions. We present efficient training and decoding algorithms for the discrete-mixture HMMs (DMHMMs). Our experimental results in the air-tr...

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Bibliographische Detailangaben

Hauptverfasser:	Tsakalidis, S., Digalakis, V., Neumeyer, L.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Cepstral analysis Decoding Distributed computing Hidden Markov models Quantization Service oriented architecture Speech recognition Web sites Working environment noise World Wide Web
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