@techreport{oai:ipsj.ixsq.nii.ac.jp:00074032,
 author = {松尾, 宏規 and 西田, 昌史 and 古谷遼 and 南條浩輝 and 山本, 誠一 and Hiroki, Matsuo and Masafumi, Nishida and Ryo, Furutani and Hiroaki, Nanjo and Seiichi, Yamamoto},
 issue = {5},
 month = {May},
 note = {音声入力型の情報検索では検索クエリ中の重要語句を正確に認識する必要があり，それらの認識誤りを少なくすることが重要である．しかし，従来の音声情報検索においては尤度最大化音声認識が用いられており，単語誤りについて考慮されていない．そこで本研究では，単語誤り率の最小化を行うベイズリスク最小化音声認識を音声入力による大学情報検索システムに導入した．本手法の有効性を示すために評価実験を行った結果，従来の尤度最大化音声認識に比べてベイズリスク最小化音声認識により音声認識精度ならびに検索精度を改善することができた．, In information retrieval based on spoken queries, it is important to recognize words in the spoken queries correctly. However, the conventional information retrievals based on spoken queries have not taken recognition errors into account because it has used the speech recognition based on maximum likelihood estimation. We propose a collage information retrieval system based on minimum Bayes-risk decording which minimizes the word error rate. To evaluate effectiveness of the proposed method, we conducted experiments. From experimental results, we demonstrated that the proposed method can improve the speech recognition accuracy and information retrieval accuracy compared with the conventional speech recognition based on maximum likelihood estimation.},
 title = {音声入力型大学情報検索システムに対するベイズリスク最小化音声認識の適用},
 year = {2011}
}