| Item type |
会議発表論文 / Conference Paper(1) |
| 公開日 |
2023-03-02 |
| タイトル |
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|
タイトル |
7感情の強度推定結果に基づく音響的特徴からの話者感情の推定手法 |
| タイトル |
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タイトル |
Speaker’s mental state estimation method using intensities of seven emotions calculated from acoustic features |
|
言語 |
en |
| 言語 |
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|
言語 |
jpn |
| 資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_5794 |
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資源タイプ |
conference paper |
| 著者 |
上村, 譲史
新升, 悠太
目良, 和也
黒澤, 義明
竹澤, 寿幸
UEMURA, Joji
SHINMASU, Yuta
MERA, Kazuya
KUROSAWA, Yoshiaki
TAKEZAWA, Toshiyuki
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| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
Previous multi-class emotion classification method has two problems; it cannot deal with emotions except pre-defined emotions, and it cannot express situation when multiple emotions are arousing at the same time. In this paper, we apply hard and soft clustering methods into emotion classification. Hard clustering method gives information to re-classify emotion classes. Soft clustering method is valid to detect data which arouse multiple emotions. Seven types of emotion voice data (anger, anticipation, disgust, fear, joy, sadness, and surprise) are re-classified into eight clusters based on intensity values of the seven emotions calculated from acoustic features. The result of hard clustering suggested that some emotion data can be classified more finely. On the other hand, some data which have the features of multiple emotions could be found by soft clustering method. |
| 書誌情報 |
人工知能学会全国大会論文集
巻 30,
p. 1-3,
発行日 2016-06
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| 出版者 |
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出版者 |
人工知能学会 |
| 関連サイト |
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識別子タイプ |
URI |
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関連識別子 |
https://www.ai-gakkai.or.jp/ |
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関連名称 |
https://www.ai-gakkai.or.jp/ |
| フォーマット |
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内容記述タイプ |
Other |
|
内容記述 |
application/pdf |
| 著者版フラグ |
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出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
JSAI2016uemura.pdf (280.7 kB)
