The Research of Speech Emotion Recognition Based on Gaussian Mixture Model

被引：2

作者：

Zhang, Wanli ^{[1
]}

Li, Guoxin ^{[1
]}

Gao, Wei ^{[2
]}

机构：

[1] Changchun Univ, Dept Elect Informat & Engn, Changchun 130022, Peoples R China

[2] Changchun Univ Finance & Econ, Dept Informat Engn, Changchun 130122, Peoples R China

来源：

MECHANICAL COMPONENTS AND CONTROL ENGINEERING III | 2014年 / 668-669卷

关键词：

Speech Emotion Recognition; Gaussian Mixture Model; Mel Frequency Cepstrum Coefficient; Feature Extraction;

D O I：

10.4028/www.scientific.net/AMM.668-669.1126

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

A new recognition method based on Gaussian mixture model for speech emotion recognition is proposed in this paper. To improve the effectiveness of feature extraction and accuracy of emotion recognition, extraction of Mel frequency cepstrum coefficient combined with Gaussian mixture model is used to recognize speech emotion. According to feature parameters extraction method by analyzing the principle of vocalization theory, emotion models based on Gaussian mixture model are generated and the similarity of their templates is obtained. A series of experiments is performed with recorded speech based on Gaussian mixture model and indicates the system gains high performance and better robustness.

引用

页码：1126 / +

页数：2