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 311–320 of 2041 papers

Title	Date	Tasks	Status	Hype	Score
SDR-GNN: Spectral Domain Reconstruction Graph Neural Network for Incomplete Multimodal Learning in Conversational Emotion Recognition	Nov 29, 2024	Emotion RecognitionGraph Neural Network	CodeCode Available	1	5
ECPE-2D: Emotion-Cause Pair Extraction based on Joint Two-Dimensional Representation, Interaction and Prediction	Jul 1, 2020	Emotion-Cause Pair ExtractionEmotion Recognition	CodeCode Available	1	5
Do You Remember? Overcoming Catastrophic Forgetting for Fake Audio Detection	Aug 7, 2023	Continual LearningEmotion Recognition	CodeCode Available	1	5
BiosERC: Integrating Biography Speakers Supported by LLMs for ERC Tasks	Jul 5, 2024	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1	5
HoloFace: Augmenting Human-to-Human Interactions on HoloLens	Feb 1, 2018	AttributeEmotion Recognition	CodeCode Available	0	5
Attentive Modality Hopping Mechanism for Speech Emotion Recognition	Nov 29, 2019	Emotion ClassificationEmotion Recognition	CodeCode Available	0	5
A multimodal dynamical variational autoencoder for audiovisual speech representation learning	May 5, 2023	DenoisingDisentanglement	CodeCode Available	0	5
A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classification	Jan 11, 2021	Causal Emotion EntailmentCausal Inference	CodeCode Available	0	5
Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and Beyond	Nov 6, 2018	Action LocalizationData Augmentation	CodeCode Available	0	5
Hierarchical Sparse and Collaborative Low-Rank Representation for Emotion Recognition	Oct 7, 2014	Emotion RecognitionGeneral Classification	CodeCode Available	0	5

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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