Hidden Markov models merging acoustic and articulatory information to automatic speech recognition
نویسندگان
چکیده
This paper describes a new scheme for robust speech recognition systems where visual information and acoustic features are merged. Using as robust unit the « pseudo-diphone », we compare a global Hidden Markov Model (HMM) and a Master/Slave HMM through a centisecond preprocessing and through a segmental one. We confirm by experimentation the importance of articulatory features in clean and noisy environments.
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