Sentence emotion recognition based on Ren-CECps

カテゴリ: 部門大会

論文No: GS15-5

グループ名: 【C】平成21年電気学会電子・情報・システム部門大会講演論文集

発行日: 2009/09/03

タイトル(英語): Sentence emotion recognition based on Ren-CECps

著者名: Changqin Quan(徳島大学),Fuji Ren(徳島大学)

著者名(英語): Changqin Quan(The University of Tokushima),Fuji Ren(The University of Tokushima)

キーワード: emotion recognition|Ren-CECps|natural language processing|affective computing

要約(日本語): There is plenty of evidence that emotion analysis has many valuable applications. In this study we propose a method of emotion recognition at sentence level based on a relative large emotion annotation corpus (Ren-CECps). From this corpus, we can get the emotion lexicons for the eight basic emotions (expect, joy, love, surprise, anxiety, sorrow, angry and hate). Statistics show that the emotion lexicons derived from Ren-CECps are used more often in real use of language for emotional expressions than HOWNET sentimental lexicons. Kernel methods are state-of-the-art for solving machine learning problems. Polynomial kernel (PK) method is used to compute the similarities between sentences and the eight emotion lexicons. Then the experiential knowledge derived from Ren-CECps is used to recogonize whether the eight emotion categories are present in a sentence.

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