[1]李 鹤,冉 妮,王 蔚.基于知识图谱的语音情感识别研究分析[J].计算机技术与发展,2020,30(06):135-140.[doi:10. 3969 / j. issn. 1673-629X. 2020. 06. 026]
　LI He,RAN Ni,WANG Wei.Research and Analysis of Speech Emotion Recognition Based on Knowledge Map[J].COMPUTER TECHNOLOGY AND DEVELOPMENT,2020,30(06):135-140.[doi:10. 3969 / j. issn. 1673-629X. 2020. 06. 026]
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基于知识图谱的语音情感识别研究分析()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年06期
页码:
135-140
栏目:
应用开发研究
出版日期:
2020-06-10

文章信息/Info

Title:
Research and Analysis of Speech Emotion Recognition Based on Knowledge Map
文章编号:
1673-629X(2020)06-0135-06
作者:
李 鹤; 冉 妮; 王 蔚
南京师范大学 教育科学学院,江苏 南京 210097
Author(s):
LI He; RAN Ni; WANG Wei
School of Education Science,Nanjing Normal University,Nanjing 210097,China
关键词:
语音情感识别; 语音知识图谱; 可视化分析; 语音情感识别系统; 情感计算
Keywords:
speech emotion recognition; knowledge map; visual analysis; speech emotion recognition system; affective computing
分类号:
H107
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 06. 026
摘要:
语言是人类相互交流与表达意图的一种自然工具,每个民族都有自己独特的语言。语音情感识别是理解人类情感表达的重要途径,已引起了以人为中心的计算机研究的广泛关注, 具有越来越高的应用价值和广泛的应用范围。因此,基于知识图谱,从语音情感识别的发展历程,研究热点,作者、机构、国家发文情况、国际合作关系等角度进行可视化分析与计量统计,并对这一领域进行较全面系统的分析,为语音情感识别的发展趋势提供参考。文献来源于可靠且覆盖全世界文献的Web Of Science 数据库, 可视化软件选用广泛使用的 Citespace。实践表明:中国发文量领先,研究储备力量雄厚,但在国际影响力上相对不足;随着人工智能的发展,语音情感识别技术难题不断突破,深度学习已被广泛应用于语音情感识别并蓬勃发展。
Abstract:
Language is a natural means of human communication and expression. Each nation has its own unique language. Speech emotion recognition which is an important way of human emotion behavior understanding has attracted extensive attention of human-centered computer research in the past decades and has more and more application value. Therefore,based on knowledge map,visual analysis and quantitative statistics are carried out from the perspectives of the development process,research hotspots,authors,institutions,national publications and international cooperative relations of speech emotion recognition. Then we make a comprehensive and systematic analysis of this field so as to provide a reference for the development trend of speech emotion recognition. The literature is from the Web Of Science database which is reliable and covers the literature of the world,and the visualization software is Citespace which is widely used. The results mainly show that China leads the world in publishing volume with a strong research reserve but relatively insufficient international influence,and with the development of artificial intelligence,deep learning has been applied in speech emotion recognition and developed vigorously.

相似文献/References:

[1]石瑛 胡学钢 方磊.基于决策树的多特征语音情感识别[J].计算机技术与发展,2009,(01):147.
　SHI Ying,HU Xue-gang,FANG Lei.Research of Speech Emotion Recognition Based on Decision Tree and Acoustic Features[J].COMPUTER TECHNOLOGY AND DEVELOPMENT,2009,(06):147.
[2]王健,韩志艳.基于正交实验设计的语音情感识别参数优化[J].计算机技术与发展,2013,(03):109.
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[3]王富,孙林慧,苏敏,等.基于参数寻优决策树SVM 的语音情感识别[J].计算机技术与发展,2018,28(07):63.[doi:10.3969/ j. issn.1673-629X.2018.07.014]
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[5]吴俊清,倪建成,魏媛媛.语音情感识别中面向小数据集的 CGRU 方法[J].计算机技术与发展,2020,30(12):77.[doi:10. 3969 / j. issn. 1673-629X. 2020. 12. 014]
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更新日期/Last Update: 2020-06-10