Riki Yoshida, Takuya Hiraoka, Graham Neubig, S. Sakti, T. Toda, Satoshi Nakamura
{"title":"Unnecessary utterance detection for avoiding digressions in discussion","authors":"Riki Yoshida, Takuya Hiraoka, Graham Neubig, S. Sakti, T. Toda, Satoshi Nakamura","doi":"10.1109/APSIPA.2014.7041572","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a method for avoiding digressions in discussion by detecting unnecessary utterances and having a dialogue system intervene. The detector is based on the features using word frequency and topic shifts. The performance (i.e. accuracy, recall, precision, and F-measure) of the unnecessary utterance detector is evaluated through leave-one-dialogue-out cross-validation. In the evaluation, we find that the performance of the proposed detector is higher than that of a typical automatic summarization method.","PeriodicalId":231382,"journal":{"name":"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPA.2014.7041572","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we propose a method for avoiding digressions in discussion by detecting unnecessary utterances and having a dialogue system intervene. The detector is based on the features using word frequency and topic shifts. The performance (i.e. accuracy, recall, precision, and F-measure) of the unnecessary utterance detector is evaluated through leave-one-dialogue-out cross-validation. In the evaluation, we find that the performance of the proposed detector is higher than that of a typical automatic summarization method.