Cross phone state clustering using lexical stress and context

This study deals with acoustic phonetic modelling in HMM based continuous speech recognition. Context dependent phone models were derived by a decision tree clustering algorithm. In particular, lexical stress was introduced as a clustering variable in addition to the phonetic context. The parameter sharing model was extended by tying HMM states across different target phones. For instance, one or more states of a tense vowel and the corresponding lax vowel were tied if they proved to be acoustically similar. The results indicate that the use of lexical stress information in acoustic modelling might be fruitful when large amounts of training data are available.