Detection of Emotions from Speech using Deep Learning Techniques and Traditional Techniques: A Survey
文献类型： 会议论文
第一作者： Rashmi Rani
作者： Rashmi Rani 1 ; Manoj Kumar Ramaiya 1 ;
作者机构： 1.Department of Computer Science and Engineering, Sage University, Indore (Affiliated to AICTE), Indore, India
关键词： Deep learning;Emotion recognition;Recurrent neural networks;Weapons;Hidden Markov models;Speech recognition;Task analysis
会议名称： International Conference on Automation, Computing and Renewable Systems
主办单位：
页码： 1202-1209
摘要： Detection of emotions from speech data is an important but exigent task of Human-Computer Communication. Speech Emotion Recognition system is a hybrid model that analyses and detect emotions embedded in speech signals. Emotion detection is a prominent task as emotions are instinctive in nature. Recently, various technologies are used to extract emotions from speech databases including traditional approaches for Speech Emotion Recognition (SER). As a substitute to traditional techniques in SER, Deep Learning techniques is great weapon to deal with the challenges in SER. This paper presents a brief review on various Deep Learning techniques and throws light on some latest literature relating to speech-based emotion recognition system.
分类号： tp3
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