This paper describes a language modeling method using large-scale spoken language data retrieved from the Web for spontaneous speech recognition. We downloaded 15 million Web pages on a comprehensive range topics. Next, spoken language- like texts were selected from the downloaded Web data using the naïve Bayes classifier, and typical linguistic phenomena such as fillers and pauses were added using simulation models. A language model trained by the generated data gave as high performance as the large-scale spontaneous speech corpus (Corpus of Spontaneous Japanese, CSJ). By combining the generated data and CSJ, we improved word accuracy.
|ジャーナル||Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH|
|出版ステータス||Published - 2011|
|イベント||12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy|
継続期間: 2011 8月 27 → 2011 8月 31
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