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- Sato Nobuo
- Advanced Research Laboratory, Hitachi, Ltd.
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- Obuchi Yasunari
- Central Research Laboratory, Hitachi, Ltd.
この論文をさがす
抄録
In this paper, we propose a new approach to emotion recognition. Prosodic features are currently used in most emotion recognition algorithms. However, emotion recognition algorithms using prosodic features are not sufficiently accurate. Therefore, we focused on the phonetic features of speech for emotion recognition. In particular, we describe the effectiveness of Mel-frequency Cepstral Coefficients (MFCCs) as the feature for emotion recognition. We focus on the precise classification of MFCC feature vectors, rather than their dynamic nature over an utterance. To realize such an approach, the proposed algorithm employs multi-template emotion classification of the analysis frames. Experimental evaluations show that the proposed algorithm produces 66.4% recognition accuracy in speaker-independent emotion recognition experiments for four specific emotions. This recognition accuracy is higher than the accuracy obtained by the conventional prosody-based and MFCC-based emotion recognition algorithms, which confirms the potential of the proposed algorithm.
収録刊行物
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- 自然言語処理
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自然言語処理 14 (4), 83-96, 2007
一般社団法人 言語処理学会
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詳細情報 詳細情報について
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- CRID
- 1390001204475902720
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- NII論文ID
- 130004291927
- 10019567971
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- NII書誌ID
- AN10472659
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- ISSN
- 21858314
- 13407619
- http://id.crossref.org/issn/13407619
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- NDL書誌ID
- 8892593
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可