4th International Conference on Spoken Language Processing
Philadelphia, PA, USA
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.
Bibliographic reference. Jacob, Bruno / Senac, Christine (1996): "Hidden Markov models merging acoustic and articulatory information to automatic speech recognition", In ICSLP-1996, 2313-2315.