删除或更新信息，请邮件至freekaoyan#163.com(#换成@)

语音情感识别中的特征选择方法

本站小编 Free考研考试/2022-01-02
-->
褚钰,李田港,叶硕,叶光明.语音情感识别中的特征选择方法[J].,2020,39(2):223-230
语音情感识别中的特征选择方法
Research on feature selection method in speech emotion recognition
投稿时间：2019-05-06修订日期：2020-02-25
中文摘要:
语音情感识别在许多领域具有重要研究价值,不同声学情感特征在使用不同分类器进行分类时,识别效果具有明显差异。与语音情感有关的声学特征包括谱特征、韵律学特征、音质特征,本文提出一种特征融合的方法,将三种声学特征中具有最好识别能力的特征进行融合：保留在实验中表现稳定且有较高识别率的谱特征的全部特征,提取韵律学、音质特征的相关统计量作为辅助特征融合于谱特征中。实验表明,本文所提出的融合特征在在使用同一分类器进行分类时,识别率优于单一特征；当使用不同分类器时,融合特征依然具有较好的识别能力,且识别性能稳定,三个数据集上均有较好的识别率,基本实现跨数据集识别。
英文摘要:
Speech emotion recognition is of great value in many fields. The recognition effect of different emotion acoustic features is obviously different when different classifiers are used for classification. Acoustic features related to speech emotions include spectral features, rhythmic features and quality features. This paper proposes a method of feature fusion, which combines the features of the three acoustic features with the best recognition ability: All the features of the spectral features that are stable in the experiment and have a high recognition rate are retained, and the relevant statistics of the rhythmic features and quality features are extracted as auxiliary features and integrated into the spectral features. Experiments show that the fusion feature proposed in this paper is better than the single feature when using the same classifier for classification; when using different classifiers, the fusion feature still has better recognition ability and stable recognition performance. It has better recognition rate on three data sets and basically realizes cross-dataset recognition.
DOI：10.11684/j.issn.1000-310X.2020.02.007
中文关键词:语音识别情感识别特征选择特征融合
英文关键词:speech recognitionemotion recognitionfeature selectionfeature fusion
基金项目:湖北省科技厅2018年度湖北省技术创新专项重大项目
作者单位E-mail
褚钰武汉邮电科学研究院18811309895@163.com
李田港武汉邮电科学研究院15038739378@163.com
叶硕武汉邮电科学研究院y9055381@126.com
叶光明武汉烽火众智数字技术有限责任公司gmye@fhzz.com.cn
摘要点击次数:940
全文下载次数:644
查看全文查看/发表评论下载PDF阅读器
相关附件：附件1修改说明1修改说明1插图修改说明2修改说明3附件1
关闭








PDF全文下载地址:

http://yysx.cnjournals.cn/ch/reader/create_pdf.aspx?file_no=19072&flag=1&journal_id=yysx&year_id=2020
相关话题/武汉邮电科学研究院 声学 英文 数据 中文

Free考研考试FreeKaoYan.Com
欢迎来到Free考研考试，"为实现人生的Free而奋斗"

© 2020 FreeKaoYan! . All rights reserved.