ISCA Archive Interspeech 2005
ISCA Archive Interspeech 2005

Situation based speech recognition for structuring baseball live games

Atsushi Sako, Tetsuya Takiguchi, Yasuo Ariki

It is a difficult problem to recognize baseball live speech because the speech is rather fast, noisy, emotional and disfluent due to rephrasing, repetition, mistake and grammatical deviation caused by spontaneous speaking style. To solve these problems, we have been studied the speech recognition method incorporating the baseball game task-dependent knowledge as well as an announcer's emotion in commentary speech [1]. In addition, in this paper, we propose the situation prediction model based on word co-occurrence. Owing to these proposed models, speech recognition errors are effectively prevented. This method is formalized in the framework of probability theory and implemented in the conventional speech decoding (Viterbi) algorithm. The experimental results showed that the proposed approach improved the structuring and segmentation accuracy as well as keywords accuracy.

doi: 10.21437/Interspeech.2005-311

Cite as: Sako, A., Takiguchi, T., Ariki, Y. (2005) Situation based speech recognition for structuring baseball live games. Proc. Interspeech 2005, 3453-3456, doi: 10.21437/Interspeech.2005-311

  author={Atsushi Sako and Tetsuya Takiguchi and Yasuo Ariki},
  title={{Situation based speech recognition for structuring baseball live games}},
  booktitle={Proc. Interspeech 2005},