情感语音处理识别用户的情绪状态进行分析，说话方式。
Emotional speech processing recognizes the user's emotional state by analyzing speech patterns.
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。
Emotion recognition of speech is signification for artificial intelligence research; the feature parameters distillate accuracy influences recognition-rate directly.
论文重点研究了基于BP神经网络的语音情感识别。
The paper has conducted the research focusing on speech emotion recognition based on BP neural network.
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。
Experiment results show the new method significantly improves accuracy of emotion classification and recognition in speech.
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。
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.
然后利用神经网络识别汉语语音中的四类基本情感(愤怒、高兴、悲伤和害怕)，取得了52.6%的平均识别率。
Neural network are used to recognize the four basic human emotions including anger, happiness, sadness and fear in speech, and we achieve an average recognition rate of approximately 52.6%.
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 new method of speech emotion recognition via voting combination of multiple classifiers is proposed for improving speech emotion classification rate.
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。
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.
分别利用普通话情感语音库和德语情感语音库进行实验，结果表明，与几种传统融合算法相比，改进的排序式选举法能够取得更好的融合效果，其识别性能明显优于单分类器。
According to the continuous space model for emotion, an improved queuing voting algorithm was proposed to implement the fusion of multiple emotion classifiers for a good emotion recognition result.
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。
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。
Speech emotion recognition is an important branch of emotion computing domain, which has been studied by many researchers from different perspectives.
分别利用语音的短时和长时特征识别说话者的五种情感状态，即生气、高兴、悲伤、惊奇和一种无情感状态。
Two kinds of speech features, long-term and short-term features are studied, to classify five emotional states: anger, happiness, sadness, surprise and a neutral state.
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。
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。
Automatic speech emotion recognition is a new research area with a wide range of applications in human-machine interactions.
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