口語表現に対応した知識ベースと連想メカニズムによる感情判断手法

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Estimation of an emotion from an uttered text is one of the most important method for natural conversations between human and robot. Most of conventional methods can only deal with a simple sentence. However, many variations of colloquial expressions are observed in natural conversations. In order to deal with such expressions, we improve the conventional emotion estimation method, which is based on the association mechanism.First, adverb and interjection are considered. The conventional method only deal with adjective and noun. However, colloquial expressions sometimes have several adverbs and interjections, and these words represent an emotion. For example, the word ``excellent has joyful emotion. Therefore, emotion labels are given to many adverbs and interjections, and used for emotion estimation of sentences.Second, complex grammars can be considered. The conventional method assumes that the input sentence has a simple sentence and only one ``emotional word is included. However, a colloquial expression may have many ``emotional words and may be a compound sentence or a complex sentence. In the proposed method, the sentence structure is analyzed, and the last ``emotional word is used for estimation because the last part is the most important in Japanese sentence. Finally, emotion estimation rules are updated.In order to investigate the effectiveness of the proposed method, emotion estimation experiments were carried out. 315 sentences were selected from utterances in a Japanese movie, and 15 evaluators gave an emotion label for each sentence. Average of agreement ratio among evaluators was 42.3%. Experimental results showed that estimation accuracy given by the proposed method was 31.4%. It was 10 points higher than the conventional estimation method, and achieved 74.2% of human ability.

口語表現に対応した知識ベースと連想メカニズムによる感情判断手法

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