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 951–960 of 2041 papers

Title	Date	Tasks	Status	Hype
Non-Contrastive Self-supervised Learning for Utterance-Level Information Extraction from Speech	Aug 10, 2022	Alzheimer's Disease DetectionEmotion Recognition	—Unverified	0
Non-Contrastive Self-Supervised Learning of Utterance-Level Speech Representations	Aug 10, 2022	Emotion RecognitionSelf-Supervised Learning	CodeCode Available	1
Emotion Detection From Tweets Using a BERT and SVM Ensemble Model	Aug 9, 2022	Emotion Recognition	CodeCode Available	0
A Novel Enhanced Convolution Neural Network with Extreme Learning Machine: Facial Emotional Recognition in Psychology Practices	Aug 5, 2022	Emotion RecognitionFacial Emotion Recognition	—Unverified	0
Domain Specific Wav2vec 2.0 Fine-tuning For The SE&R 2022 Challenge	Jul 29, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	0
Extending RNN-T-based speech recognition systems with emotion and language classification	Jul 28, 2022	Emotion ClassificationEmotion Recognition	—Unverified	0
Contextual Information and Commonsense Based Prompt for Emotion Recognition in Conversation	Jul 27, 2022	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1
A Two-Stage Efficient 3-D CNN Framework for EEG Based Emotion Recognition	Jul 26, 2022	EEGElectroencephalogram (EEG)	—Unverified	0
Multimodal Speech Emotion Recognition using Cross Attention with Aligned Audio and Text	Jul 26, 2022	Emotion RecognitionSpeech Emotion Recognition	—Unverified	0
GA2MIF: Graph and Attention Based Two-Stage Multi-Source Information Fusion for Conversational Emotion Detection	Jul 25, 2022	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1

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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