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 921–930 of 2041 papers

Title	Date	Tasks	Status	Hype
DialogueEIN: Emotion Interaction Network for Dialogue Affective Analysis	Oct 1, 2022	Emotion RecognitionEmotion Recognition in Conversation	—Unverified	0
Using Extracted Emotion Cause to Improve Content-Relevance for Empathetic Conversation Generation	Oct 1, 2022	Emotion Recognition	—Unverified	0
基于关系图注意力网络和宽度学习的负面情绪识别方法(Negative Emotion Recognition Method Based on Rational Graph Attention Network and Broad Learning)	Oct 1, 2022	Emotion RecognitionGraph Attention	—Unverified	0
Fine-tuning Wav2vec for Vocal-burst Emotion Recognition	Oct 1, 2022	Emotion Recognition	—Unverified	0
End-to-End Label Uncertainty Modeling in Speech Emotion Recognition using Bayesian Neural Networks and Label Distribution Learning	Sep 30, 2022	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available	0
CEFER: A Four Facets Framework based on Context and Emotion embedded features for Implicit and Explicit Emotion Recognition	Sep 28, 2022	Emotion RecognitionSentence	—Unverified	0
An Application of a Runtime Epistemic Probabilistic Event Calculus to Decision-making in e-Health Systems	Sep 26, 2022	Decision MakingEmotion Recognition	—Unverified	0
Song Emotion Recognition: a Performance Comparison Between Audio Features and Artificial Neural Networks	Sep 24, 2022	Emotion Recognition	—Unverified	0
Dynamic Time-Alignment of Dimensional Annotations of Emotion using Recurrent Neural Networks	Sep 21, 2022	Emotion Recognition	—Unverified	0
FV2ES: A Fully End2End Multimodal System for Fast Yet Effective Video Emotion Recognition Inference	Sep 21, 2022	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	1

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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