@article{oai:nagoya.repo.nii.ac.jp:00013600,
 author = {Hara, Sunao and Kitaoka, Norihide and Takeda, Kazuya},
 journal = {12th Annual Conference of the International Speech Communication Association in Florence, Italy, on August 27-31, 2011 (INTERSPEECH 2011)},
 month = {Aug},
 note = {We propose a method of detecting “task incomplete” dialogs in spoken dialog systems using N-gram-based dialog models. We used a database created during a field test in which inexperienced users used a client-server music retrieval system with a spoken dialog interface on their own PCs. In this study, the dialog for a music retrieval task consisted of a sequence of user and system tags that related their utterances and behaviors. The dialogs were manually classified into two classes: the dialog either completed the music retrieval task or it didn’t. We then detected dialogs that did not complete the task, using N-gram probability models or a Support Vector Machine with N-gram feature vectors trained using manually classified dialogs. Off-line and on-line detection experiments were conducted on a large amount of real data, and the results show that our proposed method achieved good classification performance.},
 pages = {1305--1308},
 title = {Detection of task-incomplete dialogs based on utterance-and-behavior tag N-gram for spoken dialog systems},
 year = {2011}
}