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 391–400 of 2041 papers

Title	Date	Tasks	Status	Score
Filter-based multi-task cross-corpus feature learning for speech emotion recognition	Feb 20, 2024	Cross-corpusEmotion Recognition	CodeCode Available	5
A novel policy for pre-trained Deep Reinforcement Learning for Speech Emotion Recognition	Jan 4, 2021	Cross-corpusDeep Reinforcement Learning	CodeCode Available	5
Fine-grained Speech Sentiment Analysis in Chinese Psychological Support Hotlines Based on Large-scale Pre-trained Model	May 7, 2024	Emotion RecognitionMulti-Label Classification	CodeCode Available	5
CoMuMDR: Code-mixed Multi-modal Multi-domain corpus for Discourse paRsing in conversations	Jun 10, 2025	Discourse ParsingEmotion Recognition	CodeCode Available	5
FeedForward at SemEval-2024 Task 10: Trigger and sentext-height enriched emotion analysis in multi-party conversations	Jun 20, 2024	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	5
CochCeps-Augment: A Novel Self-Supervised Contrastive Learning Using Cochlear Cepstrum-based Masking for Speech Emotion Recognition	Feb 10, 2024	Contrastive LearningEmotion Recognition	CodeCode Available	5
FedMultimodal: A Benchmark For Multimodal Federated Learning	Jun 15, 2023	Emotion RecognitionFederated Learning	CodeCode Available	5
FerNeXt: Facial Expression Recognition Using ConvNeXt with Channel Attention	Oct 20, 2023	Deep LearningEmotion Classification	CodeCode Available	5
Feature-Based Dual Visual Feature Extraction Model for Compound Multimodal Emotion Recognition	Mar 21, 2025	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	5
Multi-modal Speech Emotion Recognition via Feature Distribution Adaptation Network	Oct 29, 2024	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available	5

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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