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摘要: 在利用全局特征进行语音情感特征分析的基础上,提出了采用情感语句中各元音时序 结构作为新的特征,并针对不同语句中包含不同元音个数的情况,提出了零补齐、分局均值补 齐、前均值补齐三种不同的规整方法.以从10名话者中搜集的带有欢快、愤怒、惊奇、悲伤4种 情感的1000句语句作为样本,本文对语音情感特征进行了分析.实验结果表明利用全局特征和 时序特征相结合,对时序特征采用前均值补齐,同时使用修正二次判别函数(MQDF)进行情感 识别能够获得94%的平均情感识别率.Abstract: While the former method for emotional feature analysis in speech signal utilizes global features, a novel method that is based on time sequence feature is proposed in this paper. For different number of vowels, three programming methods are proposed to normalize the length of the speech signal. Experiments are conducted on a task of 10 speakers, 1000 sentences including happy, anger, surprise and sorrowful emotions to demonstrate the effectiveness of the new method. The average recognition rate is as high as 94%.
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