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.
接着，在特征提取方面尝试了一种较新的组合形式，仿真实验结果表明将多种特征参数进行合理组合有助于提高说话人识别系统的正确识别率。
Thirdly, a new combined form of feature parameters was attempted in the thesis, and reasonably compounding Characteristic parameters has been proved helpful in improving the correct recognition rate.
该方案利用数字混合信号与常用数字调制信号在信号频谱以及星座点的差异提取特征参数进行自动识别。
In the scheme, a set of feature parameters are extracted from signal spectrum and constellation based on the differences between digital mixed signals and common digital modulation signals.
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