Integrating articulatory information into stochastic segment models for continuous Mandarin speech recognition.

This paper proposed a framework which attempted to incorporate articulatory information into the stochastic segment model based on Mandarin speech recognition system. According to the characteristics of the stochastic segment model, it used hierarchical artificial neural network to obtain the posterior probability of speech signal belonging to the phonemes. Then, it integrated the posterior probability into the stochastic segment model system in the first search process. Experiments conducted on "863-test" set show that about 5.93% relative improvement could be achieved in the recognition accuracy. Thus, it demonstrates the feasibility of the method. [ABSTRACT FROM AUTHOR]