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 1261–1270 of 2041 papers

Title	Date	Tasks	Status
EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue Systems	Nov 16, 2021	Emotion RecognitionTask-Oriented Dialogue Systems	—Unverified
Emotion analysis and detection during COVID-19	Nov 16, 2021	Emotion Recognition	—Unverified
All in One: A Multi-Task Learning for Emoji, Sentiment and Emotion Analysis in Code-Mixed Text	Nov 16, 2021	AllEmotion Recognition	—Unverified
Biologically inspired speech emotion recognition	Nov 15, 2021	Emotion RecognitionSpeech Emotion Recognition	—Unverified
Speech Emotion Recognition Using Deep Sparse Auto-Encoder Extreme Learning Machine with a New Weighting Scheme and Spectro-Temporal Features Along with Classical Feature Selection and A New Quantum-Inspired Dimension Reduction Method	Nov 13, 2021	ClassificationDimensionality Reduction	—Unverified
Multilingual and Multilabel Emotion Recognition using Virtual Adversarial Training	Nov 11, 2021	Emotion RecognitionMultilabel Text Classification	—Unverified
Multimodal End-to-End Group Emotion Recognition using Cross-Modal Attention	Nov 10, 2021	Emotion RecognitionMultimodal Emotion Recognition	—Unverified
Deep Convolution Network Based Emotion Analysis for Automatic Detection of Mild Cognitive Impairment in the Elderly	Nov 9, 2021	Emotion RecognitionFacial Expression Recognition	—Unverified
Grassmannian learning mutual subspace method for image set recognition	Nov 8, 2021	Emotion RecognitionFace Identification	—Unverified
Leveraging Sentiment Analysis Knowledge to Solve Emotion Detection Tasks	Nov 5, 2021	Emotion RecognitionSentiment Analysis	—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