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 1171–1180 of 2041 papers

Title	Date	Tasks	Status	Hype
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	0
A Discourse-Aware Graph Neural Network for Emotion Recognition in Multi-Party Conversation	Nov 1, 2021	Emotion RecognitionEmotion Recognition in Conversation	—Unverified	0
Past, Present, and Future: Conversational Emotion Recognition through Structural Modeling of Psychological Knowledge	Nov 1, 2021	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1
Knowledge-Interactive Network with Sentiment Polarity Intensity-Aware Multi-Task Learning for Emotion Recognition in Conversations	Nov 1, 2021	Emotion RecognitionEmotion Recognition in Conversation	—Unverified	0
Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations	Nov 1, 2021	Emotion RecognitionEmpathetic Response Generation	—Unverified	0
Speech Emotion Recognition Using Quaternion Convolutional Neural Networks	Oct 31, 2021	Emotion RecognitionSpeech Emotion Recognition	—Unverified	0
Fusing ASR Outputs in Joint Training for Speech Emotion Recognition	Oct 29, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
End-to-End Speech Emotion Recognition: Challenges of Real-Life Emergency Call Centers Data Recordings	Oct 28, 2021	Deep LearningEmotion Recognition	—Unverified	0
Facial Emotion Recognition: A multi-task approach using deep learning	Oct 28, 2021	Deep LearningEmotion Recognition	CodeCode Available	0
MEmoBERT: Pre-training Model with Prompt-based Learning for Multimodal Emotion Recognition	Oct 27, 2021	DiversityEmotion Classification	—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