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 231–240 of 2041 papers

Title	Date	Tasks	Status
TGCA-PVT: Topic-Guided Context-Aware Pyramid Vision Transformer for Sticker Emotion Recognition	Oct 28, 2024	Emotion Recognition	CodeCode Available
Improving Speech-based Emotion Recognition with Contextual Utterance Analysis and LLMs	Oct 27, 2024	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
A Survey on Speech Large Language Models	Oct 24, 2024	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Emotion Recognition with Facial Attention and Objective Activation Functions	Oct 23, 2024	Emotion RecognitionFacial Emotion Recognition	—Unverified
Enhancing Multimodal Affective Analysis with Learned Live Comment Features	Oct 21, 2024	Contrastive LearningEmotion Recognition	—Unverified
MMDS: A Multimodal Medical Diagnosis System Integrating Image Analysis and Knowledge-based Departmental Consultation	Oct 20, 2024	Emotion RecognitionFacial Emotion Recognition	—Unverified
Regularized Xception for facial expression recognition with extra training data and step decay learning rate	Oct 17, 2024	Emotion RecognitionFacial Emotion Recognition	CodeCode Available
Investigating Effective Speaker Property Privacy Protection in Federated Learning for Speech Emotion Recognition	Oct 17, 2024	Emotion RecognitionFederated Learning	—Unverified
SeQuiFi: Mitigating Catastrophic Forgetting in Speech Emotion Recognition with Sequential Class-Finetuning	Oct 16, 2024	Continual LearningEmotion Recognition	—Unverified
Multi-View Multi-Task Modeling with Speech Foundation Models for Speech Forensic Tasks	Oct 16, 2024	Age EstimationEmotion Recognition	—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