• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 论文 • 上一篇    下一篇

融合语音情感词局部特征的语音情感识别方法

宋明虎,余正涛,高盛祥,李铚,沈韬   

  1. (昆明理工大学信息工程与自动化学院,云南 昆明 650500)
  • 收稿日期:2015-09-16 修回日期:2015-12-21 出版日期:2017-01-25 发布日期:2017-01-25
  • 基金资助:

    国家自然科学基金(61175068);科技部科技创新领军人才推进计划(2014HE001)

Speech emotion recognition integrating
local features of sentiment words

SONG Minghu,YU Zhengtao,GAO Shengxiang,LI Zhi,SHENG Tao   

  1. (School of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China)
  • Received:2015-09-16 Revised:2015-12-21 Online:2017-01-25 Published:2017-01-25

摘要:

为有效利用语音情感词局部特征,提出了一种融合情感词局部特征与语音语句全局特征的语音情感识别方法。该方法依赖于语音情感词典的声学特征库,提取出语音语句中是否包含情感词及情感词密度等局部特征,并与全局声学特征进行融合,再通过机器学习算法建模和识别语音情感。对比实验结果表明,融合语音情感词局部特征与全局特征的语音情感识别方法能取得更好的效果,局部特征的引入能有效提高语音情感识别准确率。
 

关键词: 语音, 情感识别, 语音情感词典, 局部特征, 全局特征

Abstract:

To improve efficient utilization of local features in sentiment words of speech, we propose a new speech emotion recognition method by fusing local features of sentiment words and global features. Based on the acoustic features of the emotional dictionary, we extract local features, such as sentiment word existence in the statement and its density. Then by fusing the global features of speech, we can recognize the speech emotion through modeling with machine learning algorithms. The comparative experiment results show that the proposed method can gain very good performance, and the introduction of local features can improve the precision of speech emotion recognition.

Key words: speech, emotion recognition, speech emotion dictionary, local feature, global feature