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発話状態時間長に着目した対話雰囲気推定
https://nitech.repo.nii.ac.jp/records/3640
https://nitech.repo.nii.ac.jp/records/3640b0fbac51-4cab-466c-b1a7-dd33bd1727f6
名前 / ファイル | ライセンス | アクション |
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本文_fulltext (334.3 kB)
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Copyright(2012) 人工知能学会
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2013-06-25 | |||||
タイトル | ||||||
タイトル | 発話状態時間長に着目した対話雰囲気推定 | |||||
言語 | ||||||
言語 | jpn | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
その他(別言語等)のタイトル | ||||||
その他のタイトル | ハツワ ジョウタイ ジカンチョウ 二 チャクモク シタ タイワ フンイキ スイテイ | |||||
その他(別言語等)のタイトル | ||||||
その他のタイトル | Dialogue Mood Estimation Focusing on Intervals of Utterance State | |||||
著者 |
豊田, 薫
× 豊田, 薫× 宮越, 喜浩× 山西, 良典× 加藤, 昇平 |
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著者別名 | ||||||
姓名 | Kato, Shohei | |||||
書誌情報 |
人工知能学会論文誌 巻 27, 号 2, p. 16-21, 発行日 2012 |
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出版者 | ||||||
出版者 | 人工知能学会 | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 13460714 | |||||
書誌レコードID(NCID) | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA11579226 | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
DOI | ||||||
関連タイプ | isIdenticalTo | |||||
識別子タイプ | DOI | |||||
関連識別子 | http://dx.doi.org/10.1527/tjsai.27.16 | |||||
関連名称 | 10.1527/tjsai.27.16 | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | In the field of the communication robots, many recent studies have focused on dialogue communication robots. This paper especially focused on the supporting robot for the conversation between humans. To help conversation between humans, we believe that the robots should have two abilities: estimate dialogue moods and behave suitably. In this paper, we propose dialogue moods estimation model. This paper, as the first step, focused on dialogues between two persons and construct estimation model for the dialogue moods observed by the third party. Because we believed that the dialogue moods are influenced by utterance time, which is extracted easily, the utterance intervals features are used to estimate the dialogue moods, for example, both solitary utterance intervals of leading speakers and following speakers, simultaneous utterance intervals, and silent intervals between two speakers. Using these utterance intervals features, we constructed the estimation model for dialogue moods by using Tree-Augmented Naive Bayes. Through the estimation experiment, we confirmed the availability of the estimation model for dialogue moods, in particular ``excitement,'' ``seriousness,'' and ``closeness,'' and the effective utterance intervals features for estimating dialogue moods. From the experimental results, it is suggested that the proposed model is effective for estimating dialogue moods. | |||||
フォーマット | ||||||
内容記述タイプ | Other | |||||
内容記述 | application/pdf |