| 3. | Firstly , we study the construction of emotion - speech template database , and analyze the common features such as pitch , energy and formant . after choosing the useful features by using fuzzy entropy effectiveness analysis , we get better performance with the application of neural network . in addition , we propose some more efficient features such as speech rate , pitch slope , mel - frequency cepstral coefficients and its transient parameters , and design a processing model based on vector quantization for cepstral features to fusing different features
本文首先介绍了情感语音数据库的建立情况,然后研究了基音频率、振幅能量和共振峰等目前常用的情感特征在语音情感识别中的作用,并且通过一种基于模糊熵的特征有效性分析方法进行了有效特征的筛选,应用人工神经网络建立了初步的语音情感识别模型,经过实验发现特征筛选后系统的识别效果有着一定程度的提高。 |
