A Large-Vocabulary Bilingual Speech Recognition System for Chinese and Japanese Language

Bilingual or Multilingual speech recognition gradually becomes an attractive research topic because bilingual writings appear almost everywhere in present day. In this paper, we propose a continuous word-based speech recognition system to dictate the Mandarin and Japanese speech simultaneously. We find that there are about 62 basic phoneme like units(PLUs) among the mixed Mandarin and Japanese syllables. The 62 HA/Ms are used to decode the input speech into word hypotheses based on a fast tree-beam searching algorithm. In the language model, the bigram model and trigram model are used to select the most likely word from the word candidates. We also have a bilingual dictionary to deal with the cross language information. Our proposed system architecture can not only dictate Mandarin and Japanese speech simultaneously but also provide a possible solution to recognize any other bilingual speech. I