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 2011–2020 of 2041 papers

Title	Date	Tasks	Status
Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain Adaptation	Nov 19, 2024	Domain AdaptationEEG	CodeCode Available
End-to-End Multimodal Emotion Recognition using Deep Neural Networks	Apr 27, 2017	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available
Unsupervised Cross-Lingual Speech Emotion Recognition Using Pseudo Multilabel	Aug 19, 2021	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available
The Many Faces of Anger: A Multicultural Video Dataset of Negative Emotions in the Wild (MFA-Wild)	Dec 10, 2021	Cultural Vocal Bursts Intensity PredictionEmotion Classification	CodeCode Available
Analysis of the Evolution of Advanced Transformer-Based Language Models: Experiments on Opinion Mining	Aug 7, 2023	Emotion RecognitionOpinion Mining	CodeCode Available
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
ML-PersRef: A Machine Learning-based Personalized Multimodal Fusion Approach for Referencing Outside Objects From a Moving Vehicle	Nov 3, 2021	Emotion Recognitionmultimodal interaction	CodeCode Available
End-To-End Label Uncertainty Modeling for Speech-based Arousal Recognition Using Bayesian Neural Networks	Oct 7, 2021	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available
EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue Systems	Sep 10, 2021	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available
MMCert: Provable Defense against Adversarial Attacks to Multi-modal Models	Mar 28, 2024	Emotion RecognitionRoad Segmentation	CodeCode Available

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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