[1]韩天翊,林荣恒.一种基于决策层融合的多模态情感识别方法[J].南京师范大学学报(工程技术版),2022,(02):035-40.[doi:10.3969/j.issn.1672-1292.2022.02.006]
 Han Tianyi,Lin Rongheng.A Multimodal Emotion Recognition Method Based on Decision Level Fusion[J].Journal of Nanjing Normal University(Engineering and Technology),2022,(02):035-40.[doi:10.3969/j.issn.1672-1292.2022.02.006]
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一种基于决策层融合的多模态情感识别方法
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南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2022年02期
页码:
035-40
栏目:
计算机科学与技术
出版日期:
2022-06-30

文章信息/Info

Title:
A Multimodal Emotion Recognition Method Based on Decision Level Fusion
文章编号:
1672-1292(2022)02-0035-06
作者:
韩天翊12林荣恒12
(1.北京邮电大学计算机学院(国家示范性软件学院),北京 100876)(2.北京邮电大学网络与交换技术国家重点实验室,北京 100876)
Author(s):
Han Tianyi12Lin Rongheng12
(1.School of Computer Science(National Pilot Software Engineering School),Beijing University of Posts and Telecommunications,Beijing 100876,China)(2.State Key Laboratory of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China)
关键词:
情感识别卷积神经网络软硬结合多模态决策层融合
Keywords:
emotion recognitionconvolutional neural networkcombination of software and hardwaremultimodaldecision-level fusion
分类号:
TP391
DOI:
10.3969/j.issn.1672-1292.2022.02.006
文献标志码:
A
摘要:
设计了一种软硬结合的多模态情感识别系统,使用语音和面部表情两个模态,通过梅尔频率倒谱系数与卷积神经网络对情感进行识别和分类,同时将语音情感识别迁移到神经网络计算棒以降低环境负载. 在模态融合时,采用决策层融合的方式来提高识别准确率. 实验结果表明,系统拥有较高的识别准确率,且能够在性能较差的运行环境中保持运行速度.
Abstract:
This paper designs a multimodal emotion recognition system that combines software and hardware. The system uses Mel-Frequency Cepstrum Coefficient and convolutional neural networks to recognize and classify emotions on speech and facial expressions. At the same time,emotion recognition of speech is transferred to neural network computing sticks to reduce the environmental load. In modal fusion,the method of decision-level fusion is used to improve the recognition accuracy. Experimental results show that the system has high recognition accuracy and can maintain running speed in the environment with poor performance.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2021-08-31.
基金项目:江西省重点研发计划项目(20212BBE51002).
通讯作者:林荣恒,博士,副教授,研究方向:强化学习与生成对抗研究、云计算边缘计算、工业大数据分析、大数据与人工智能. E-mail:rhlin@bupt.edu.cn
更新日期/Last Update: 1900-01-01