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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1611–1620 of 2041 papers

Title	Date	Tasks	Status
A Time Series Analysis of Emotional Loading in Central Bank Statements	Nov 26, 2019	Emotion RecognitionTime Series	—Unverified
Atom Search Optimization with Simulated Annealing -- a Hybrid Metaheuristic Approach for Feature Selection	May 10, 2020	Emotion RecognitionFacial Emotion Recognition	—Unverified
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition	Aug 6, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
A Transformer Architecture for Stress Detection from ECG	Aug 22, 2021	Emotion Recognition	—Unverified
Attention-based Region of Interest (ROI) Detection for Speech Emotion Recognition	Mar 3, 2022	Emotion RecognitionMulti-class Classification	—Unverified
Attention Driven Fusion for Multi-Modal Emotion Recognition	Sep 23, 2020	Emotion ClassificationEmotion Recognition	—Unverified
Attentive Convolutional Neural Network based Speech Emotion Recognition: A Study on the Impact of Input Features, Signal Length, and Acted Speech	Jun 2, 2017	Emotion RecognitionMULTI-VIEW LEARNING	—Unverified
Attentive Cross-modal Connections for Deep Multimodal Wearable-based Emotion Recognition	Aug 4, 2021	ClassificationEmotion Classification	—Unverified
Attributes-aware Visual Emotion Representation Learning	Apr 9, 2025	AttributeEmotion Recognition	—Unverified
AttX: Attentive Cross-Connections for Fusion of Wearable Signals in Emotion Recognition	Jun 9, 2022	Emotion RecognitionRepresentation Learning	—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