Syllable Models for Mandarin Speech Recognition: Exploiting Character Language Models

TitleSyllable Models for Mandarin Speech Recognition: Exploiting Character Language Models
Publication TypeJournal Article
Year of Publication2013
AuthorsLiu, X., Hieronymus J., Gales M.. J. F., & Woodland P.
Published inJournal of the Acoustical Society of America
Volume133
Issue1
Page(s)519-528
Other Numbers3310
Abstract

Mandarin Chinese is based on characters which are syllabic in nature and morphological in meaning. All spoken languages have syllabiotactic rules which govern the construction of syllables and their allowed sequences. These constraints are not as restrictive as those learned from word sequences, but they can provide additional useful linguistic information. Hence, it is possible to improve speech recognition performance by appropriately combining these two types of constraints. For the Chinese language considered in this paper, character level language models (LMs) can be used as a first level approximation to allowed syllable sequences. To test this idea, word and character level n-gram LMs were trained on 2.8 billion words (equivalent to 4.3 billion characters) of texts from a wide collection of text sources. Both hypothesis and model based combination techniques were investigated to combine word and character level LMs. Significant character error rate reductions up to 7.3% relative were obtained on a state-of-the-art Mandarin Chinese broadcast audio recognition task using an adapted history dependent multi-level LM that performs a log-linearly combination of character and word level LMs. This supports the hypothesis that character or syllable sequence models are useful for improving Mandarin speech recognition performance.

Bibliographic Notes

Journal of the Acoustical Society of America, Vol. 133, No. 1, pp. 519-528

Abbreviated Authors

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

ICSI Research Group

Speech

ICSI Publication Type

Article in journal or magazine