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 741–750 of 2041 papers

Title	Date	Tasks	Status	Hype
GEmo-CLAP: Gender-Attribute-Enhanced Contrastive Language-Audio Pretraining for Accurate Speech Emotion Recognition	Jun 13, 2023	AttributeContrastive Learning	—Unverified	0
MFSN: Multi-perspective Fusion Search Network For Pre-training Knowledge in Speech Emotion Recognition	Jun 12, 2023	Emotion RecognitionQuantization	—Unverified	0
Exploring Attention Mechanisms for Multimodal Emotion Recognition in an Emergency Call Center Corpus	Jun 12, 2023	Decision MakingEmotion Recognition	—Unverified	0
Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and Paraphrasing	Jun 11, 2023	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	0
Estimating the Uncertainty in Emotion Attributes using Deep Evidential Regression	Jun 11, 2023	AttributeEmotion Recognition	CodeCode Available	1
TS-MoCo: Time-Series Momentum Contrast for Self-Supervised Physiological Representation Learning	Jun 10, 2023	Activity RecognitionClassification	CodeCode Available	1
Modality Influence in Multimodal Machine Learning	Jun 10, 2023	Decision MakingEmotion Recognition	—Unverified	0
Learning Emotional Representations from Imbalanced Speech Data for Speech Emotion Recognition and Emotional Text-to-Speech	Jun 9, 2023	Emotion RecognitionSpeech Emotion Recognition	—Unverified	0
A Quantum Probability Driven Framework for Joint Multi-Modal Sarcasm, Sentiment and Emotion Analysis	Jun 6, 2023	Decision MakingEmotion Recognition	—Unverified	0
Synthesizing Affective Neurophysiological Signals Using Generative Models: A Review Paper	Jun 5, 2023	Data AugmentationEEG	—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