Exploiting Chinese Character Models to Improve Speech Recognition Performance

TitleExploiting Chinese Character Models to Improve Speech Recognition Performance
Publication TypeConference Paper
Year of Publication2009
AuthorsHieronymus, J., Liu X., Gales M.. J. F., & Woodland P.
Other Numbers3312
Abstract

The Chinese language is based on characters which are syllabic in nature. Since languages have syllabotactic rules which govern the construction of syllables and their allowed sequences, Chinese character sequence models can be used as a first level approximation of allowed syllable sequences. N-gram character sequence models were trained on 4.3 billion characters. Characters are used as a first level recognition unit with multiple pronunciations per character. For comparison the CU-HTK Mandarin word based system was used to recognize words which were then converted to character sequences. The character only system error rates for one best recognition were slightly worse than word based character recognition. However combining the two systems using log-linear combination gives better results than either system separately. An equally weighted combination gave consistent CER gains of 0.1-0.2% absolute over the word based standard system.

Bibliographic Notes

Proceedings of the 10th Annual Conference of the International Speech Communication Association (Interspeech 2009), Brighton, United Kingdom

Abbreviated Authors

J. L. Hieronymus, X. Liu, M. J. F. Gales, and P. C. Woodland

ICSI Research Group

Speech

ICSI Publication Type

Article in conference proceedings