基于支持向量机的人类语音和面部情感识别技术

Meaad Hussein Abdul-Hadi, Jumana Waleed
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引用次数: 6

摘要

语言和面部表情是人类认知交流和识别人类身份和情感状态最重要的信息载体。随着计算机处理能力的进一步提高和智能生活需求的增加,基于人脸和语音的情感识别成为人机交互(HCI)应用中最重要的领域。为了有效提高多情绪检测的性能,本文提出了一种基于人类语音和面部的支持向量机(SVM)情感识别技术。实验结果表明,该方法的平均识别率高于现有的其他方法,人脸模型的识别率为92.88%,语音模型的识别率为85.72%,且耗时短。
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Human Speech and Facial Emotion Recognition Technique Using SVM
Human Speech and Facial are the most significant information carriers for human cognitive-communication and recognizing human’s identity and emotional status. With the further growth of computer processing capability and the increase of demand for intelligent living, recognition of emotion based on face and speech became the most significant in the applications of Human-Computer Interaction (HCI). In this paper, Human Speech and Facial based emotion recognition technique using a support vector machine (SVM) has been proposed for improving the performance of detection with multi-emotions effectively. The obtained results of the proposed technique show that the average rate of recognition is higher than other recently existing techniques, and the obtained accuracy is 92.88% for facial model and 85.72 % for speech model with low time-consuming.
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