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 191–200 of 2041 papers

Title	Date	Tasks	Status	Hype
Enhanced Speech Emotion Recognition with Efficient Channel Attention Guided Deep CNN-BiLSTM Framework	Dec 13, 2024	Emotion RecognitionSpeech Emotion Recognition	—Unverified	0
Multimodal Sentiment Analysis based on Video and Audio Inputs	Dec 12, 2024	Decision MakingEmotion Recognition	—Unverified	0
EmoVerse: Exploring Multimodal Large Language Models for Sentiment and Emotion Understanding	Dec 11, 2024	Depression DetectionEmotion-Cause Pair Extraction	CodeCode Available	1
My Words Imply Your Opinion: Reader Agent-Based Propagation Enhancement for Personalized Implicit Emotion Analysis	Dec 10, 2024	Emotion RecognitionGraph Learning	—Unverified	0
Depression detection from Social Media Bangla Text Using Recurrent Neural Networks	Dec 8, 2024	Depression DetectionEmotion Recognition	—Unverified	0
WavFusion: Towards wav2vec 2.0 Multimodal Speech Emotion Recognition	Dec 7, 2024	DiversityEmotion Recognition	—Unverified	0
Dynamic Graph Neural ODE Network for Multi-modal Emotion Recognition in Conversation	Dec 4, 2024	Emotion RecognitionEmotion Recognition in Conversation	—Unverified	0
VR Based Emotion Recognition Using Deep Multimodal Fusion With Biosignals Across Multiple Anatomical Domains	Dec 3, 2024	Emotion RecognitionFeature Importance	—Unverified	0
Swin Transformer with Enhanced Dropout and Layer-wise Unfreezing for Facial Expression Recognition in Mental Health Detection	Dec 2, 2024	Emotion RecognitionFacial Emotion Recognition	CodeCode Available	1
Cross-Task Inconsistency Based Active Learning (CTIAL) for Emotion Recognition	Dec 2, 2024	Active LearningCross-corpus	—Unverified	0

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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