A survey of speech emotion recognition in natural environment

MS Fahad, A Ranjan, J Yadav, A Deepak - Digital signal processing, 2021 - Elsevier
While speech emotion recognition (SER) has been an active research field since the last
three decades, the techniques that deal with the natural environment have only emerged in …

A survey of emotion recognition methods with emphasis on E-Learning environments

M Imani, GA Montazer - Journal of Network and Computer Applications, 2019 - Elsevier
Emotions play an important role in the learning process. Considering the learner's emotions
is essential for electronic learning (e-learning) systems. Some researchers have proposed …

Speech emotion recognition using deep neural network and extreme learning machine

K Han, D Yu, I Tashev - Interspeech 2014, 2014 - microsoft.com
Speech emotion recognition is a challenging problem partly because it is unclear what
features are effective for the task. In this paper we propose to utilize deep neural networks …

Domain invariant feature learning for speaker-independent speech emotion recognition

C Lu, Y Zong, W Zheng, Y Li, C Tang… - … /ACM Transactions on …, 2022 - ieeexplore.ieee.org
In this paper, we propose a novel domain invariant feature learning (DIFL) method to deal
with speaker-independent speech emotion recognition (SER). The basic idea of DIFL is to …

Survey on audiovisual emotion recognition: databases, features, and data fusion strategies

CH Wu, JC Lin, WL Wei - APSIPA transactions on signal and …, 2014 - cambridge.org
Emotion recognition is the ability to identify what people would think someone is feeling from
moment to moment and understand the connection between his/her feelings and …

Speaker-sensitive emotion recognition via ranking: Studies on acted and spontaneous speech

H Cao, R Verma, A Nenkova - Computer speech & language, 2015 - Elsevier
We introduce a ranking approach for emotion recognition which naturally incorporates
information about the general expressivity of speakers. We demonstrate that our approach …

Speaker-invariant affective representation learning via adversarial training

H Li, M Tu, J Huang, S Narayanan… - ICASSP 2020-2020 …, 2020 - ieeexplore.ieee.org
Representation learning for speech emotion recognition is challenging due to labeled data
sparsity issue and lack of gold-standard references. In addition, there is much variability from …

Feature selection based transfer subspace learning for speech emotion recognition

P Song, W Zheng - IEEE Transactions on Affective Computing, 2018 - ieeexplore.ieee.org
Cross-corpus speech emotion recognition has recently received considerable attention due
to the widespread existence of various emotional speech. It takes one corpus as the training …

DNN-HMM-based speaker-adaptive emotion recognition using MFCC and epoch-based features

MS Fahad, A Deepak, G Pradhan, J Yadav - Circuits, Systems, and Signal …, 2021 - Springer
Speech emotion recognition (SER) systems are often evaluated in a speaker-independent
manner. However, the variation in the acoustic features of different speakers used during …

Speech emotion recognition research: an analysis of research focus

MB Mustafa, MAM Yusoof, ZM Don… - International Journal of …, 2018 - Springer
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 …