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 611–620 of 2041 papers

Title	Date	Tasks	Status	Hype
Emotional Theory of Mind: Bridging Fast Visual Processing with Slow Linguistic Reasoning	Oct 30, 2023	Emotion RecognitionLanguage Modelling	—Unverified	0
Pre-trained Speech Processing Models Contain Human-Like Biases that Propagate to Speech Emotion Recognition	Oct 29, 2023	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available	0
Multi-label Emotion Analysis in Conversation via Multimodal Knowledge Distillation	Oct 27, 2023	Emotion RecognitionKnowledge Distillation	—Unverified	0
Privacy-preserving Representation Learning for Speech Understanding	Oct 26, 2023	ClassificationEmotion Recognition	—Unverified	0
Affective Video Content Analysis: Decade Review and New Perspectives	Oct 26, 2023	Emotional IntelligenceEmotion Recognition	—Unverified	0
Data Augmentation for Emotion Detection in Small Imbalanced Text Data	Oct 25, 2023	Data AugmentationEmotion Recognition	CodeCode Available	0
SSLCL: An Efficient Model-Agnostic Supervised Contrastive Learning Framework for Emotion Recognition in Conversations	Oct 25, 2023	Contrastive LearningEmotion Recognition	CodeCode Available	1
A Contextualized Real-Time Multimodal Emotion Recognition for Conversational Agents using Graph Convolutional Networks in Reinforcement Learning	Oct 24, 2023	Emotion ClassificationEmotion Recognition	—Unverified	0
Do Stochastic Parrots have Feelings Too? Improving Neural Detection of Synthetic Text via Emotion Recognition	Oct 24, 2023	Emotion RecognitionText Generation	CodeCode Available	0
The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages	Oct 23, 2023	Emotion RecognitionFew-Shot Learning	CodeCode Available	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