Deep learning techniques for speech emotion recognition, from databases to models
The advancements in neural networks and the on-demand need for accurate and near real-
time Speech Emotion Recognition (SER) in human–computer interactions make it …
time Speech Emotion Recognition (SER) in human–computer interactions make it …
Analysis of emotional speech—A review
P Gangamohan, SR Kadiri… - Toward Robotic Socially …, 2016 - Springer
Speech carries information not only about the lexical content, but also about the age,
gender, signature and emotional state of the speaker. Speech in different emotional states is …
gender, signature and emotional state of the speaker. Speech in different emotional states is …
Towards a small set of robust acoustic features for emotion recognition: challenges
M Tahon, L Devillers - … ACM transactions on audio, speech, and …, 2015 - ieeexplore.ieee.org
The search of a small acoustic feature set for emotion recognition faces three main
challenges. Such a feature set must be robust to large diversity of contexts in real-life …
challenges. Such a feature set must be robust to large diversity of contexts in real-life …
Emotion classification using segmentation of vowel-like and non-vowel-like regions
S Deb, S Dandapat - IEEE Transactions on Affective Computing, 2017 - ieeexplore.ieee.org
In this work, a novel region switching based classification method is proposed for speech
emotion classification using vowel-like regions (VLRs) and non-vowel-like regions (non …
emotion classification using vowel-like regions (VLRs) and non-vowel-like regions (non …
Speech emotion recognition research: an analysis of research focus
This article analyses research in speech emotion recognition (“SER”) from 2006 to 2017 in
order to identify the current focus of research, and areas in which research is lacking. The …
order to identify the current focus of research, and areas in which research is lacking. The …
Enhancing speech-based depression detection through gender dependent vowel-level formant features
Depression has been consistently linked with alterations in speech motor control
characterised by changes in formant dynamics. However, potential differences in the …
characterised by changes in formant dynamics. However, potential differences in the …
[PDF][PDF] 语音情感特征提取及其降维方法综述
刘振焘， 徐建平， 吴敏， 曹卫华， 陈略峰， 丁学文， 郝曼… - 计算机学报, 2018 - cjc.ict.ac.cn
摘要情感智能是人工智能的重要发展方向, 随着人工智能的迅速发展, 情感智能已成为当前人机
交互领域的研究热点. 语音情感是人们相互情感交流最直接, 最高效的途径 …
交互领域的研究热点. 语音情感是人们相互情感交流最直接, 最高效的途径 …
Compensating for speaker or lexical variabilities in speech for emotion recognition
S Mariooryad, C Busso - Speech Communication, 2014 - Elsevier
Affect recognition is a crucial requirement for future human machine interfaces to effectively
respond to nonverbal behaviors of the user. Speech emotion recognition systems analyze …
respond to nonverbal behaviors of the user. Speech emotion recognition systems analyze …
Modeling phonetic pattern variability in favor of the creation of robust emotion classifiers for real-life applications
The role of automatic emotion recognition from speech is growing continuously because of
the accepted importance of reacting to the emotional state of the user in human–computer …
the accepted importance of reacting to the emotional state of the user in human–computer …
An investigation of partition-based and phonetically-aware acoustic features for continuous emotion prediction from speech
Phonetic variability has long been considered a confounding factor for emotional speech
processing, so phonetic features have been rarely explored. However, surprisingly some …
processing, so phonetic features have been rarely explored. However, surprisingly some …