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首页> 外文会议>International Conference on Computational Science and Its Applications(ICCSA 2004) pt.4; 20040514-20040517; Assisi; IT >Speech Emotion Recognition and Intensity Estimation
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Speech Emotion Recognition and Intensity Estimation

机译：语音情感识别和强度估计

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摘要

In this paper, a system for speech emotion analysis is presented. On a corpus of over 1700 utterances from an individual, the feature vector stream is extracted for each utterance based on short time log frequency power coefficients (LFCC). Using the feature vector streams, we trained Hidden Markov Models (HMMs) to recognize seven basic categories emotions: neutral, happiness, anger, sadness, surprise, fear. Furthermore, the intensity of the basic emotion is divided into 3 levels. And we trained 18 sub-HMMs to identify the intensity of the recognized emotions. Experiment result shows that the emotion recognition rate and the estimation of intensity performed by our system are of good and convincing quality.
机译：本文提出了一种语音情感分析系统。在来自个人的超过1700种话语的语料库上，基于短时间对数频率功率系数（LFCC）为每种话语提取特征向量流。使用特征向量流，我们训练了隐马尔可夫模型（HMM）以识别七个基本类别的情绪：中性，幸福，愤怒，悲伤，惊奇，恐惧。此外，基本情绪的强度分为3个等级。我们训练了18个子HMM，以识别已识别情绪的强度。实验结果表明，该系统进行的情绪识别率和强度估计具有良好的说服力。

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