@techreport{oai:ipsj.ixsq.nii.ac.jp:00062357,
 author = {粟野, 健太郎 and 伊藤, 仁 and 伊藤, 彰則 and 牧野, 正三 and Kentaro, Awano and Masashi, Ito and Akinori, Ito and Shozo, Makino},
 issue = {15},
 month = {May},
 note = {本稿では複数の音声対話システムを併用することを目的とし，そのために必要な発話識別の方法を検討した．併用するシステムとして，確認応答型システムと一問一答型システムを用いた．識別の特徴量として発話の各タスクらしさを表すスコアと音声認識結果の尤度を用いた．発話識別は特徴量の大小比較とニューラルネットで行った．音声認識結果が1-best時とN-best時の両方で識別実験を行ったところ，80%以上の正解率を得るとともにN-best時の方が正解率が向上することが分かった．, We studied a method of utterance discrimination for a spoken dialog system that combines multiple dialog systems. Frame-based and example-based systems are used as systems for combination. We used similarities to tasks and likelihood obtained by a speech recognizer as features for the discrimination. A discrimination function is composed by a neural network. We conducted a discrimination experiment using 1-best and n-best recognition results of the speech recognizer. As a result, we obtained more than 80% accuracy, and the result by the n-best candidates was better than that by the 1-best candidate.},
 title = {複数の音声対話システム併用のための発話識別},
 year = {2009}
}