International audienceIn this paper, hidden Markov models (HMM)-based vowel and consonant automatic recognition in French Cued Speech is presented. Cued Speech is a visual communication mode which uses handshapes in different positions and in combination with lip-patterns of speech, makes all the sounds of spoken language clearly understandable to deaf and hearingimpaired people. The aim of Cued Speech is to overcome the problems of lipreading and thus enable deaf children and adults to fully understand a spoken language. Previously, the authors have reported experimental results on vowel recognition in Cued Speech for French based on feature fusion and multi-stream HMM decision fusion. This study, further investigates the vowel recognition by considering vowel classes based on similarities on the lips. Also automatic consonant recognition experiments in Cued Speech for French are reported. The obtained results are promising and comparable with results obtained using audio signal
