Speech Emotion Recognition under Noise Background
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摘要: 为有效实现含噪声的语音信号情感类型的识别,提出了一种基于抗噪声的模糊最小二乘支持向量机的语音情感识别新方法.该方法先提取情感语音的韵律特征和音质特征,再利用模糊最小二乘支持向量机构建最优分类超平面,实现生气、高兴、悲伤和惊奇4种情感类型的识别.试验结果表明,与其他多种语音情感识别方法相比,在不同信噪比下,新方法的情感正确识别率较高,抗噪声识别效果较好,表明了其有效性.
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关键词:
- 模糊最小二乘支持向量机 /
- 韵律特征 /
- 音质特征 /
- 情感识别
Abstract: To efficiently implement emotion recognition in noise speech signals,a new method of speech emotion recognition based on FLSSVM (fuzzy least squares support vector machines) was proposed. With this method,the prosody and voice quality features are extracted from emotional speech,and then FLSSVM is used to construct the optimum separating hyperplane so as to realize the recognition of four main speech emotions,i.e.,anger,happiness,sadness and surprise. Experimental results show that compared with the other methods of speech emotion recognition,FLSSVM can achieve higher accuracies and better anti-noise effects for speech emotion recognition at different levels of signal-to-noise ratio,indicating the efficiency of the proposed method. -
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