Unified solution for procurement integration and B2B stores
Trieu C. Chieu, Shiwa S. Fu, et al.
ICEC 2003
A new class of hidden Markov models is proposed for the acoustic representation of words in an automatic speech recognition system. The models, built from combinations of acoustically based sub-word units called fenones, are derived automatically from one or more sample utterances of a word. Because they are more flexible than previously reported fenone-based word models, they lead to an improved capability of modeling variations in pronunciation. They are therefore particularly useful in the recognition of continuous speech. In addition, their construction is relatively simple, because it can be done using the well-known forward-backward algorithm for parameter estimation of hidden Markov models. Appropriate reestimation formulas are derived for this purpose. Experimental results obtained on a 5000-word vocabulary natural language continuous speech recognition task are presented to illustrate the enhanced power of discrimination of the new models. © 1993 IEEE
Trieu C. Chieu, Shiwa S. Fu, et al.
ICEC 2003
Matt McKeon
IEEE TVCG
Aidong Lu, Christopher J. Morris, et al.
IEEE TVCG
Kun Wang, Juwei Shi, et al.
PACT 2011