A visual speech recognition system for an ultrasound-based silent speech interface
Résumé
The development of a continuous visual speech recognizer for a silent speech interface has been investigated using a visual speech corpus of ultrasound and video images of the tongue and lips. By using high-speed visual data and tied-state cross-word triphone HMMs, and including syntactic information via domain-specific language models, word-level recognition accuracy as high as 72% was achieved on visual speech. Using the Julius system, it was also found that the recognition should be possible in nearly real-time.