Taiga Kirihara, Kazuyuki Matsumoto, M. Sasayama, Minoru Yoshida, K. Kita
{"title":"访谈对话系统的话题分割","authors":"Taiga Kirihara, Kazuyuki Matsumoto, M. Sasayama, Minoru Yoshida, K. Kita","doi":"10.1145/3508230.3508237","DOIUrl":null,"url":null,"abstract":"In this study, topic segmentation was performed by referring to the interview dialogue corpus. Utterance intention tags were added to the existing interview dialogue corpus, and uttered sentences were vectorized using BERT, Sentence BERT, and Distil BERT. In addition, topic classification was performed using the utterance intention tags and the features of the preceding and following uttered sentences. Consequently, the greatest accuracy was achieved when the utterance intention tag was used with DistilBERT.","PeriodicalId":252146,"journal":{"name":"Proceedings of the 2021 5th International Conference on Natural Language Processing and Information Retrieval","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Topic Segmentation for Interview Dialogue System\",\"authors\":\"Taiga Kirihara, Kazuyuki Matsumoto, M. Sasayama, Minoru Yoshida, K. Kita\",\"doi\":\"10.1145/3508230.3508237\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, topic segmentation was performed by referring to the interview dialogue corpus. Utterance intention tags were added to the existing interview dialogue corpus, and uttered sentences were vectorized using BERT, Sentence BERT, and Distil BERT. In addition, topic classification was performed using the utterance intention tags and the features of the preceding and following uttered sentences. Consequently, the greatest accuracy was achieved when the utterance intention tag was used with DistilBERT.\",\"PeriodicalId\":252146,\"journal\":{\"name\":\"Proceedings of the 2021 5th International Conference on Natural Language Processing and Information Retrieval\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2021 5th International Conference on Natural Language Processing and Information Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3508230.3508237\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 5th International Conference on Natural Language Processing and Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3508230.3508237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this study, topic segmentation was performed by referring to the interview dialogue corpus. Utterance intention tags were added to the existing interview dialogue corpus, and uttered sentences were vectorized using BERT, Sentence BERT, and Distil BERT. In addition, topic classification was performed using the utterance intention tags and the features of the preceding and following uttered sentences. Consequently, the greatest accuracy was achieved when the utterance intention tag was used with DistilBERT.
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