Handling disynchronization phenomena with HMM in connected speech

Anticipation and retention phenomena between the different phonatory organs have been widely studied in the speech perception and production domain. However, few automatic speech recognition systems are able to handle them. In this paper, we define a product of valuated transitions automata handling these difficulties. Then, we use such automata in a recognition system based on HMM. This method is evaluated in two different contexts : bimodal and unimodal speech recognition. The results show an improvement for the the product model against a synchronous one of 1.9% in the bimodal field and of 1.2% in the unimodal one.