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 961–970 of 2041 papers

Title	Date	Tasks	Status
Fine-tuning Wav2vec for Vocal-burst Emotion Recognition	Oct 1, 2022	Emotion Recognition	—Unverified
Fitting Different Interactive Information: Joint Classification of Emotion and Intention	Jan 5, 2025	Emotion RecognitionIntent Detection	—Unverified
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition	Aug 6, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Focal Loss based Residual Convolutional Neural Network for Speech Emotion Recognition	Jun 11, 2019	Emotion RecognitionSpeech Emotion Recognition	—Unverified
Human Pose Descriptions and Subject-Focused Attention for Improved Zero-Shot Transfer in Human-Centric Classification Tasks	Mar 11, 2024	Activity RecognitionAge Classification	—Unverified
CUET-NLP@TamilNLP-ACL2022: Multi-Class Textual Emotion Detection from Social Media using Transformer	May 1, 2022	Emotion RecognitionOpinion Mining	—Unverified
Forewords	Dec 1, 2017	Emotion RecognitionIntent Classification	—Unverified
Fractal Dimension Pattern Based Multiresolution Analysis for Rough Estimator of Person-Dependent Audio Emotion Recognition	Jul 1, 2016	Audio Emotion RecognitionEmotion Recognition	—Unverified
An Approach for Improving Automatic Mouth Emotion Recognition	Dec 12, 2022	Emotion Recognition	—Unverified
Dual Prototyping with Domain and Class Prototypes for Affective Brain-Computer Interface in Unseen Target Conditions	Nov 27, 2024	Brain Computer InterfaceDisentanglement	—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