ISCA Archive ICSLP 2000
ISCA Archive ICSLP 2000

Effects of word string language models on noisy broadcast news speech recognition

Kazuyuki Takagi, Rei Oguro, Kazuhiko Ozeki

In this paper, we present the results that our n-gram based word string language model, combined with speaker and noise adaptation of the acoustic model, improves recognition performance of noisy broadcast news speech. The focus was brought into a remedy against recognition errors of short words. The word string language models based on POS and n-gram fre- quency reduced deletion errors by 17%, insertion errors by 20%, and substitution errors by 3% in Japanese TV broadcast news speech recognition.


Cite as: Takagi, K., Oguro, R., Ozeki, K. (2000) Effects of word string language models on noisy broadcast news speech recognition. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 1, 154-157

@inproceedings{takagi00_icslp,
  author={Kazuyuki Takagi and Rei Oguro and Kazuhiko Ozeki},
  title={{Effects of word string language models on noisy broadcast news speech recognition}},
  year=2000,
  booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
  pages={vol. 1, 154-157}
}