ISCA Archive ICSLP 2000
ISCA Archive ICSLP 2000

Acoustic modeling for spontaneous speech recognition using syllable dependent models

Toshiyuki Hanazawa, Jun Ishii, Yohei Okato, Kunio Nakajima

This paper proposes a syllable context dependent model for spontaneous speech recognition. It is generally assumed that, since spontaneous speech is greatly affected by coarticulation, an acoustic model featuring a longer range phonemic context is required to achieve a high degree of recognition accuracy. This motivated the authors to investigate a tri-syllable model that takes differences in the preceding and succeeding syllables into account. Since Japanese syllables consist of either a single vowel or a consonant and vowel combination, a tri-syllable model always takes the preceding and succeeding vowels that are the primary factors in coarticulation into account. A tri-syllable model is thus capable of efficiently representing coarticulation. The tri-syllable model was trained using spontaneous speech; then, the effectiveness of continuous syllable recognition and statistical language model-based continuous word recognition were evaluated. Compared to a regular triphone model without state sharing, it was found that the correct syllable accuracy of the continuous syllable recognition improved from 64.9% to 66.3%. The word recognition accuracy for the statistical language modelbased continuous word recognition improved from 88.4% to 89.2%.


Cite as: Hanazawa, T., Ishii, J., Okato, Y., Nakajima, K. (2000) Acoustic modeling for spontaneous speech recognition using syllable dependent models. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 4, 157-160

@inproceedings{hanazawa00b_icslp,
  author={Toshiyuki Hanazawa and Jun Ishii and Yohei Okato and Kunio Nakajima},
  title={{Acoustic modeling for spontaneous speech recognition using syllable dependent models}},
  year=2000,
  booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
  pages={vol. 4, 157-160}
}