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A General Method for Combining Acoustic Features in an Automatic Speech Recognition System

Abstract : A general method for the use of different types of fea- tures in Automatic Speech Recognition (ASR) systems is presented. A gaussian mixture model (GMM) is ob- tained in a reference acoustic space. A specific fea- ture combination or selection is associated to each gaus- sian of the mixture and used for computing symbol pos- terior 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 vocab- ularies in Italian and Spanish and one with very large vocabulary in French.
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https://hal.archives-ouvertes.fr/hal-00433108
Contributor : Loïc Barrault <>
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Driss Matrouf, Loïc Barrault, Renato de Mori. A General Method for Combining Acoustic Features in an Automatic Speech Recognition System. ITRW on Speech Recognition and Intrinsic Variation, May 2006, Toulouse, France. pp.N/A. ⟨hal-00433108⟩

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