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

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Showing 41–50 of 2041 papers

Title	Date	Tasks	Status	Hype
Are We There Yet? A Brief Survey of Music Emotion Prediction Datasets, Models and Outstanding Challenges	Jun 13, 2024	Emotion RecognitionMusic Emotion Recognition	CodeCode Available	2
A Survey of Personalized Large Language Models: Progress and Future Directions	Feb 17, 2025	Emotion RecognitionGeneral Knowledge	CodeCode Available	2
audino: A Modern Annotation Tool for Audio and Speech	Jun 9, 2020	Action DetectionActivity Detection	CodeCode Available	2
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT	Oct 7, 2023	Audio captioningAutomatic Speech Recognition	CodeCode Available	2
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversation	Aug 26, 2021	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1
Compact Graph Architecture for Speech Emotion Recognition	Aug 5, 2020	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available	1
CoMPM: Context Modeling with Speaker’s Pre-trained Memory Tracking for Emotion Recognition in Conversation	Jul 1, 2022	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal Nuances	Jul 31, 2024	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1
Accuracy enhancement method for speech emotion recognition from spectrogram using temporal frequency correlation and positional information learning through knowledge transfer	Mar 26, 2024	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available	1
COGMEN: COntextualized GNN based Multimodal Emotion recognitioN	May 5, 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