Emotion recognition of speech is signification for artificial intelligence research; the feature parameters distillate accuracy influences recognition-rate directly.
语音情感识别是人工智能的重要研究领域之一，特征参数提取的准确性直接影响识别的效果。
A new method of speech emotion recognition via voting combination of multiple classifiers is proposed for improving speech emotion classification rate.
为了提高语音情感的正确识别率，提出一种基于多分类器投票组合的语音情感识别新方法。
A speech emotion recognition method is also presented based on weighted Euclidean distance template matching, in which the weights of features are calculated by the method of contribution analysis.
同时提出采用贡献分析法确定情感特征参数的权值，利用加权欧氏距离模板匹配识别语音情感。
The paper has conducted the research focusing on speech emotion recognition based on BP neural network.
论文重点研究了基于BP神经网络的语音情感识别。
Experiment results show the new method significantly improves accuracy of emotion classification and recognition in speech.
实验结果证明这种新的方法有效地提高了语音情感识别的准确率。
In the field of speech emotion recognition, the emotion features of different emotional utterances are commonly extracted at same segment length level.
语音情感识别领域提取情感特征时，普遍采用“不同情感类别，相同时长基准”的做法，忽略了人耳敏感的韵律段长会依情感不同而有所差异的现象。
Speech emotion recognition is an important branch of emotion computing domain, which has been studied by many researchers from different perspectives.
语音情感识别是情感计算领域的一个重要分支，研究者们尝试从多种角度对其展开不懈研究。
Automatic speech emotion recognition is a new research area with a wide range of applications in human-machine interactions.
基于语音的自动人类情感识别是近年来新兴的研究课题，它在人机通信中有广阔的应用前景。
The entropy series and neurons firing series of the image obtained by feeding the spectrogram into PCNN were used as the characteristics of emotion speech for emotion recognition.
该方法将语音转化为语谱图后输入到PCNN，得到输出图像的神经元点火序列及其熵序列作为语音情感的特征，利用其特征实现语音情感识别。
Research on Emotion Recognition from Speech-Features and Models;
有无法控制的兴奋或情感的特征。
Research on Emotion Recognition from Speech-Features and Models;
有无法控制的兴奋或情感的特征。
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