Speech Emotional Recognition Using Global and Time Sequence Structure Features with MMD
Speech Emotional Recognition Using Global and Time Sequence Structure Features with MMD
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DOI：
10.1007/11573548_40
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发表时间：
2005-10
期刊：
影响因子：
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通讯作者：
Li Zhao;Yujia Cao;Zhiping Wang;C. Zou
中科院分区：
文献类型：
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作者：
Li Zhao;Yujia Cao;Zhiping Wang;C. Zou
本文采用全局特征和时间序列特征相结合的方法作为语音情绪识别的特征参数。提出了一种基于修正马氏距离（MMD）公式的新方法，减小了估计误差，简化了计算。本文考虑了快乐、愤怒、惊讶和悲伤四种情绪。从10位说话者那里收集了1000个识别句子来证明新方法的有效性。平均情绪识别率达到95%。与MQDF[1]（修正二次判别函数）方法比较，数据分析也表明，MMD方法优于MQDF方法。
In this paper, combined features of global and time-sequence were used as the characteristic parameters for speech emotional recognition. A new method based on formula of MMD (Modified Mahalanobis Distance) was proposed to decrease the estimated errors and simplify the calculation. Four emotions including happiness, anger, surprise and sadness are considered in the paper. 1000 recognizing sentences collected from 10 speakers were used to demonstrate the effectiveness of the new method. The average emotion recognition rate reached at 95%. Comparison with method of MQDF [1] (Modified quadratic discriminant function), Data analysis also displayed that the MMD is better than MQDF.