In speech recognition systems, a common problem is transcription of new additions to the recognition lexicon into their phonetic symbols. Specific to the Japanese language, such a problem can be dealt with in two steps. In this paper, we focus on the first step, in which the new lexical entry is converted into a set of hiragana syllabaries, which is almost a phonetic transcription. We propose a conversion scheme which yields the most likely hiragana syllabaries, based on a language model. Results from our evaluations on three test sets are also reported. Although the study is conducted on Japanese only, our approach has applications to Chinese.
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