.png){kind=icon}
返回
Speech Emotion Recognition Using Deep Learning Techniques: A Review
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2019.2936124.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Emotion recognition from speech signals is an important but challenging component of Human-Computer Interaction (HCI). In the literature of speech emotion recognition (SER), many techniques have been utilized to extract emotions from signals, including many well-established speech analysis and classification techniques. Deep Learning techniques have been recently proposed as an alternative to traditional techniques in SER. This paper presents an overview of Deep Learning techniques and discusses some recent literature where these methods are utilized for speech-based emotion recognition. The review covers databases used, emotions extracted, contributions made toward speech emotion recognition and limitations related to it.
Keyword:
Speech emotion recognition
deep learning
deep neural network
deep Boltzmann machine
recurrent neural network
deep belief network
convolutional neural network
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
Emotion Recognition from Chinese Speech for Smart Affective Services Using a Combination of SVM and DBN使用SVM和DBN的组合从中文语音中识别情感以实现智能情感服务.png)
SENSORSOAAI
SENSORSIF3.5
OAAI分享收藏Improved Particle Size Control for the Dispersion Polymerization of Methyl methacrylate in Supercritical Carbon Dioxide超临界二氧化碳中甲基丙烯酸甲酯分散聚合的改进粒度控制OAAI
OAAI分享收藏分享收藏
查看更多内容