Emotion Recognition

Emotion Recognition is an important area of research to enable effective human-computer interaction. Human emotions can be detected using speech signal, facial expressions, body language, and electroencephalography (EEG). Source: Using Deep Autoencoders for Facial Expression Recognition

Papers

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Showing 571–580 of 2041 papers

Title	Date	Tasks	Status
Effective Context Modeling Framework for Emotion Recognition in Conversations	Dec 21, 2024	Emotion Recognition	—Unverified
Characterizing Types of Convolution in Deep Convolutional Recurrent Neural Networks for Robust Speech Emotion Recognition	Jun 7, 2017	Emotion RecognitionEvent Detection	—Unverified
Annotated Corpus of Tweets in English from Various Domains for Emotion Detection	Dec 1, 2020	Emotion Recognition	—Unverified
A Computational Analysis of Mahabharata	Dec 1, 2016	Emotion Recognition	—Unverified
CG-MER: A Card Game-based Multimodal dataset for Emotion Recognition	Jan 14, 2025	Emotion Recognition	—Unverified
An Iterative Emotion Interaction Network for Emotion Recognition in Conversations	Dec 1, 2020	Emotion RecognitionEmotion Recognition in Conversation	—Unverified
EEG-based Multimodal Representation Learning for Emotion Recognition	Oct 29, 2024	EEGElectroencephalogram (EEG)	—Unverified
CEFER: A Four Facets Framework based on Context and Emotion embedded features for Implicit and Explicit Emotion Recognition	Sep 28, 2022	Emotion RecognitionSentence	—Unverified
CAT: Credibility Analysis of Arabic Content on Twitter	Apr 1, 2017	Emotion RecognitionOpinion Mining	—Unverified
4D Attention-based Neural Network for EEG Emotion Recognition	Jan 14, 2021	Brain Computer InterfaceEEG	—Unverified

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All datasets Emomusic RAVDESS EMOTIC FER2013 MaSaC_ERC MPED MSP-Podcast SEED คลิปคุณพ่อให้ลูกสาวยืมโทรศัพท์และความสนุกสนาน

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	M2D-CLAP	EmoA	77.4	—	Unverified
2	M2D2	EmoA	76.7	—	Unverified
3	M2D	EmoA	76.1	—	Unverified
4	Jukebox (Pre-training: CALM)	EmoA	72.1	—	Unverified
5	CLMR (Pre-training: contrastive)	EmoA	67.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LogisticRegression on posteriors of xlsr-Wav2Vec2.0&bi-LSTM+Attention	Accuracy	86.7	—	Unverified
2	MultiMAE-DER	WAR	83.61	—	Unverified
3	Intermediate-Attention-Fusion	Accuracy	81.58	—	Unverified
4	Logistic Regression on posteriors of the CNN-14&biLSTM-GuidedST	Accuracy	80.08	—	Unverified
5	ERANN-0-4	Accuracy	74.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CAGE	Top-3 Accuracy (%)	14.73	—	Unverified
2	FocusCLIP	Top-3 Accuracy (%)	13.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VGG based	5-class test accuracy	66.13	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MaSaC-ERC-Z	F1-score (Weighted)	51.17	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BiHDM	Accuracy	40.34	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	w2v2-L-robust-12	Concordance correlation coefficient (CCC)	0.64	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	4D-aNN	Accuracy	96.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN	1'"	1	—	Unverified