Expanding vocabulary for recognizing user's abbreviations of proper nouns without increasing ASR error rates in spoken dialogue systems

Users often abbreviate long words when using spoken dialogue systems, which results in automatic speech recognition (ASR) errors. We define abbreviated words as sub-words of the original word, and add them into an ASR dictionary. The first problem is that proper nouns cannot be correctly segmented by general morphological analyzers, although long and compounded words need to be segmented in agglutinative languages such as Japanese. The second is that, as vocabulary increases, adding many abbreviated words degrades the ASR accuracy. We develop two methods, (1) to segment words by using conjunction probabilities between characters, and (2) to manipulate occurrence probabilities of generated abbreviated words on the basis of the phonological similarities between abbreviated and original words. By our method, the ASR accuracy is improved by 24.2 points for utterances containing abbreviated words, and degraded by only a 0.1 point for those containing original words.