Multiple pronunciation dictionary using HMM-state confusion characteristics

In this paper, we propose a POS (part-of-speech)-dependent multiple pronunciation dictionary generation method using HMM-state confusions spanning several phonemes. When used in a multi-pass search, a dictionary generated from the method makes it possible to recover missing words that are lost during the first pass of the search process in continuous speech recognition using a single pronunciation dictionary. The new pronunciations are added to a dictionary that considers the POS dependency of the confusion characteristics. Continuous word recognition experiments have confirmed that the best results are obtained when (1) confusions expressed by HMM-state sequences and (2) pronunciation variations considering the POS-dependent confusion characteristics are used.