| Summary: | 碩士 === 大同大學 === 資訊工程學系(所) === 99 === In recent years, the speech emotion recognition is one of the active topics in speech signal processing as well as human emotion research. The majority of corpus used in the speech emotion recognition researches is based on short corpus. However, in the daily human conversation, what we used are almost long sentences. Consequently, the accuracy of speech emotion recognition is low when we apply it in the real life situation. In order to improve the emotion recognition rate for long sentences and be more close to the real feeling of emotion perceived by human, we propose a method which combines the semantics of spoken word and the emotion recognized from the speech signal. The results
indicated that by combining the spoken word semantics, we can increase the recognition accuracy by 8% for various scripts as compared with those using speech emotion recognition only.
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