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 1281–1290 of 2041 papers

Title	Date	Tasks	Status	Hype
Silent Speech and Emotion Recognition from Vocal Tract Shape Dynamics in Real-Time MRI	Jun 16, 2021	Emotion RecognitionSentence	—Unverified	0
Automatic Analysis of the Emotional Content of Speech in Daylong Child-Centered Recordings from a Neonatal Intensive Care Unit	Jun 14, 2021	Active LearningBinary Classification	—Unverified	0
Tracing Back Music Emotion Predictions to Sound Sources and Intuitive Perceptual Qualities	Jun 14, 2021	Emotion RecognitionInformation Retrieval	CodeCode Available	1
Efficient Speech Emotion Recognition Using Multi-Scale CNN and Attention	Jun 8, 2021	Emotion ClassificationEmotion Recognition	CodeCode Available	1
Subject Independent Emotion Recognition using EEG Signals Employing Attention Driven Neural Networks	Jun 7, 2021	Deep LearningEEG	—Unverified	0
An Attribute-Aligned Strategy for Learning Speech Representation	Jun 5, 2021	AttributeEmotion Recognition	—Unverified	0
Musical Prosody-Driven Emotion Classification: Interpreting Vocalists Portrayal of Emotions Through Machine Learning	Jun 4, 2021	BIG-bench Machine LearningEmotion Classification	—Unverified	0
DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in Conversations	Jun 3, 2021	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1
EmoDNN: Understanding emotions from short texts through a deep neural network ensemble	Jun 3, 2021	Emotion RecognitionManagement	—Unverified	0
COIN: Conversational Interactive Networks for Emotion Recognition in Conversation	Jun 1, 2021	Emotion RecognitionEmotion Recognition in Conversation	—Unverified	0

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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