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 1751–1760 of 2041 papers

Title	Date	Tasks	Status
Convolutional neural networks pretrained on large face recognition datasets for emotion classification from video	Nov 13, 2017	Emotion ClassificationEmotion Recognition	—Unverified
Convolutional Speech Recognition with Pitch and Voice Quality Features	Sep 2, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
CoordViT: A Novel Method of Improve Vision Transformer-Based Speech Emotion Recognition using Coordinate Information Concatenate	Mar 10, 2023	Emotion RecognitionPosition	—Unverified
CopyPaste: An Augmentation Method for Speech Emotion Recognition	Oct 27, 2020	Data AugmentationEmotion Recognition	—Unverified
Cosmopolitan Mumbai, Orthodox Delhi, Techcity Bangalore:Understanding City Specific Societal Sentiment	Dec 1, 2016	Emotion Recognition	—Unverified
Could Speaker, Gender or Age Awareness be beneficial in Speech-based Emotion Recognition?	May 1, 2016	Emotion RecognitionSpoken Dialogue Systems	—Unverified
CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognition	Jun 6, 2025	Emotion RecognitionFairness	—Unverified
Cross-Attention is Not Always Needed: Dynamic Cross-Attention for Audio-Visual Dimensional Emotion Recognition	Mar 28, 2024	Emotion Recognition	—Unverified
Cross-Corpus Multilingual Speech Emotion Recognition: Amharic vs. Other Languages	Jul 20, 2023	Cross-corpusEmotion Recognition	—Unverified
Cross-cultural Emotion Classification: the Effect of Emotional Intensity and Acoustic Features	Nov 16, 2021	Cultural Vocal Bursts Intensity PredictionEmotion Classification	—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