 |
Speech Recognition and Intrinsic Variation (SRIV2006)Toulouse, France |
 |
|
Speech Recognition and Intrinsic Variation (SRIV2006)Toulouse, France |
|
A general method for the use of different types of features in Automatic Speech Recognition (ASR) systems is presented. A gaussian mixture model (GMM) is obtained in a reference acoustic space. A specific feature combination or selection is associated to each gaussian of the mixture and used for computing symbol posterior probabilities. Symbols can refer to phonemes, phonemes in context or states of a Hidden Markov Model (HMM). Experimental results are presented of applications to phoneme and word rescoring after verification. Two corpora were used, one with small vocabularies in Italian and Spanish and one with very large vocabulary in French.
Bibliographic reference. Matrouf, Driss / Barrault, Loic / Mori, Renato De (2006): "A general method for combining acoustic features in an automatic speech recognition system", In SRIV-2006, 89-94.