| 摘要 |
PROBLEM TO BE SOLVED: To generate a statistical language model, in which the prediction precision of transition probability and reliability are improved, and to conduct voice recognition with a higher voice recognition rate using the model. SOLUTION: In the device, a clustering is automatically conducted by a clustering processing section 40 for the entire learning text data and the text data for every cluster are stored in a memory 21. Then, a statistical language model for every cluster is generated by a language model generating section 42 employing an MAP estimation method and the models are stored in a memory 32. On the other hand, a statistical language model is generated for the entire learning text data and stored in a memory 31. After the generation of a word hypothesis by a word collating section 4, a word hypothesis narrowing section 6a executes a narrowing process of the word hypothesis using the model in the memory 31. Then, a language model selecting section 8 selects the model having a maximum sentence generating probability among the statistical language models of the clusters in the memory 32. Finally, a word hypothesis narrowing section 6b conducts a narrowing process again using the selected model and outputs a recognition result. |
