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 811–820 of 2041 papers

Title	Date	Tasks	Status
Leveraging Previous Facial Action Units Knowledge for Emotion Recognition on Faces	Nov 20, 2023	Emotion Recognition	—Unverified
Multi-Task Faces (MTF) Data Set: A Legally and Ethically Compliant Collection of Face Images for Various Classification Tasks	Nov 20, 2023	Age ClassificationAge Estimation	CodeCode Available
Implementation of AI Deep Learning Algorithm For Multi-Modal Sentiment Analysis	Nov 19, 2023	Emotion RecognitionSentiment Analysis	—Unverified
Utilizing Speech Emotion Recognition and Recommender Systems for Negative Emotion Handling in Therapy Chatbots	Nov 18, 2023	ChatbotEmotion Recognition	—Unverified
Enhancing Student Engagement in Online Learning through Facial Expression Analysis and Complex Emotion Recognition using Deep Learning	Nov 17, 2023	Emotion Recognition	—Unverified
Accommodating Missing Modalities in Time-Continuous Multimodal Emotion Recognition	Nov 16, 2023	Emotion RecognitionMultimodal Emotion Recognition	—Unverified
Improving Unimodal Inference with Multimodal Transformers	Nov 16, 2023	Emotion RecognitionGesture Recognition	—Unverified
On the Effectiveness of ASR Representations in Real-world Noisy Speech Emotion Recognition	Nov 13, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Exploring Emotion Expression Recognition in Older Adults Interacting with a Virtual Coach	Nov 9, 2023	Emotion Recognition	—Unverified
Wearable data from subjects playing Super Mario, sitting university exams, or performing physical exercise help detect acute mood episodes via self-supervised learning	Nov 7, 2023	Body DetectionEmotion 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