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

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Showing 141–150 of 431 papers

Title	Date	Tasks	Status	Score
Fine-grained Speech Sentiment Analysis in Chinese Psychological Support Hotlines Based on Large-scale Pre-trained Model	May 7, 2024	Emotion RecognitionMulti-Label Classification	CodeCode Available	5
ExHuBERT: Enhancing HuBERT Through Block Extension and Fine-Tuning on 37 Emotion Datasets	Jun 11, 2024	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available	5
Pretrained audio neural networks for Speech emotion recognition in Portuguese	Oct 26, 2022	Data AugmentationEmotion Recognition	CodeCode Available	5
Domain Adversarial for Acoustic Emotion Recognition	Apr 20, 2018	AttributeEmotion Recognition	—Unverified	0
Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition	Jul 7, 2022	Cross-corpusDeep Reinforcement Learning	—Unverified	0
Automated Assessment of Encouragement and Warmth in Classrooms Leveraging Multimodal Emotional Features and ChatGPT	Apr 1, 2024	Emotion RecognitionSentiment Analysis	—Unverified	0
Disentangling Prosody Representations with Unsupervised Speech Reconstruction	Dec 14, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Developing a High-performance Framework for Speech Emotion Recognition in Naturalistic Conditions Challenge for Emotional Attribute Prediction	Jun 12, 2025	AttributeEmotion Recognition	—Unverified	0
Audio Representation Learning by Distilling Video as Privileged Information	Feb 6, 2023	Emotion RecognitionKnowledge Distillation	—Unverified	0
An analysis of large speech models-based representations for speech emotion recognition	Nov 1, 2023	Emotion RecognitionSpeech Emotion Recognition	—Unverified	0

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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