Speech Emotion Recognition

Speech Emotion Recognition is a task of speech processing and computational paralinguistics that aims to recognize and categorize the emotions expressed in spoken language. The goal is to determine the emotional state of a speaker, such as happiness, anger, sadness, or frustration, from their speech patterns, such as prosody, pitch, and rhythm.

For multimodal emotion recognition, please upload your result to Multimodal Emotion Recognition on IEMOCAP

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 426–431 of 431 papers

Title	Date	Tasks	Status
Investigating salient representations and label Variance in Dimensional Speech Emotion Analysis	Dec 17, 2023	Emotion RecognitionSpeech Emotion Recognition	—Unverified
Investigating the Impact of Word Informativeness on Speech Emotion Recognition	Jun 2, 2025	Emotion RecognitionInformativeness	—Unverified
Investigations on Audiovisual Emotion Recognition in Noisy Conditions	Mar 2, 2021	Emotion RecognitionSpeech Emotion Recognition	—Unverified
Is It Still Fair? Investigating Gender Fairness in Cross-Corpus Speech Emotion Recognition	Jan 2, 2025	Cross-corpusEmotion Recognition	—Unverified
A Case Study on the Independence of Speech Emotion Recognition in Bangla and English Languages using Language-Independent Prosodic Features	Nov 21, 2021	Emotion RecognitionSpeech Emotion Recognition	—Unverified
Fine-grained Early Frequency Attention for Deep Speaker Representation Learning	Sep 3, 2020	Deep LearningEmotion Recognition	—Unverified

Show:10 25 50

← PrevPage 18 of 18Next →

All datasets CREMA-D IEMOCAP RAVDESS MSP-Podcast (Activation)MSP-Podcast (Dominance)MSP-Podcast (Valence)BERSt RESD Dusha Crowd Dusha Podcast EMODB EmoDB Dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Vertically long patch ViT	Accuracy	94.07	—	Unverified
2	ConformerXL-P	Accuracy	88.2	—	Unverified
3	CoordViT	Accuracy	82.96	—	Unverified
4	SepTr + LeRaC	Accuracy	70.95	—	Unverified
5	SepTr	Accuracy	70.47	—	Unverified
6	ResNet-18 + SPEL	Accuracy	68.12	—	Unverified
7	ViT	Accuracy	67.81	—	Unverified
8	ResNet-18 + PyNADA	Accuracy	65.15	—	Unverified
9	GRU	Accuracy	55.01	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SER with MTL	UA CV	0.78	—	Unverified
2	emoDARTS	UA CV	0.77	—	Unverified
3	LSTM+FC	WA	0.76	—	Unverified
4	TAP	WA CV	0.74	—	Unverified
5	SYSCOMB: BLSTMATT with CSA (session5)	UA	0.74	—	Unverified
6	Partially Fine-tuned HuBERT Large	WA CV	0.73	—	Unverified
7	CNN - DARTS	UA	0.7	—	Unverified
8	CNN+LSTM	UA	0.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VQ-MAE-S-12 (Frame) + Query2Emo	Accuracy	84.1	—	Unverified
2	CNN-X (Shallow CNN)	Accuracy	82.99	—	Unverified
3	xlsr-Wav2Vec2.0(FineTuning)	Accuracy	81.82	—	Unverified
4	CNN-14 (Fine-Tuning)	Accuracy	76.58	—	Unverified
5	AlexNet (FineTuning)	Accuracy	61.67	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	wav2small-Teacher	CCC	0.76	—	Unverified
2	wavlm	CCC	0.75	—	Unverified
3	w2v2-L-robust-12	CCC	0.75	—	Unverified
4	preCPC	CCC	0.71	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	wav2small-Teacher	CCC	0.68	—	Unverified
2	wavlm	CCC	0.67	—	Unverified
3	w2v2-L-robust-12	CCC	0.66	—	Unverified
4	preCPC	CCC	0.64	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	wav2small-Teacher	CCC	0.68	—	Unverified
2	wavlm	CCC	0.65	—	Unverified
3	w2v2-L-robust-12	CCC	0.64	—	Unverified
4	preCPC	CCC	0.38	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DAWN-hidden-SVM	Unweighted Accuracy (UA)	32.1	—	Unverified
2	Wav2Small-VAD-SVM	Unweighted Accuracy (UA)	23.3	—	Unverified
3	Speechbrain Wav2Vec2	Unweighted Accuracy (UA)	20.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	emotion2vec+base	Weighted Accuracy (WA)	79.4	—	Unverified
2	emotion2vec+large	Weighted Accuracy (WA)	69.5	—	Unverified
3	emotion2vec	Weighted Accuracy (WA)	64.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Dusha baseline	Macro F1	0.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Dusha baseline	Macro F1	0.54	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VGG-optiVMD	1:1 Accuracy	96.09	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VQ-MAE-S-12 (Frame) + Query2Emo	Accuracy	90.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PyResNet	Unweighted Accuracy (UA)	0.43	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	emoDARTS	UA	0.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LSTM	CCC (Arousal)	0.76	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN (1D)	Unweighted Accuracy	65.2	—	Unverified