GENERATION OF ADAPTIVE VOCABULARY LEXICON FOR JAPANESE LVCSR

One of the thorniest problems of large vocabulary continuous speech recognition systems is the large number of out-of-vocabulary (OOV) words. This is especially the case for the languages like Japanese, which has many inflections, compound words and loanwords. The OOV words vary with the application domains. It's not realistic to have a big general-purpose lexicon including any possible 00V words. Furthermore, embedded speech recognition systems become more and more popular recently. They strongly demand an economical and effective exploitation of lexicon space. In this paper, we introduce a lexicon development model dealing with different kinds of OOV words with the help of linguistic morphological knowledge. It provides unsupervised, fast vocabulary adaptation among different application domains. In the experiments that adapt a lexicon of typical vocabulary, we were able to reduce the OOV rate by 40 % and improve the word segmentation error rate by 27%. And the smaller the lexicon is, the more we benefit from the vocabulary adaptation. 1