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 31–40 of 431 papers

Title	Date	Tasks	Status	Hype
A Persian ASR-based SER: Modification of Sharif Emotional Speech Database and Investigation of Persian Text Corpora	Nov 18, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1
Temporal Modeling Matters: A Novel Temporal Emotional Modeling Approach for Speech Emotion Recognition	Nov 14, 2022	Speech Emotion Recognition	CodeCode Available	1
SPEAKER VGG CCT: Cross-corpus Speech Emotion Recognition with Speaker Embedding and Vision Transformers	Nov 4, 2022	Cross-corpusEmotion Recognition	CodeCode Available	1
GM-TCNet: Gated Multi-scale Temporal Convolutional Network using Emotion Causality for Speech Emotion Recognition	Oct 28, 2022	Emotion RecognitionRepresentation Learning	CodeCode Available	1
Speech Emotion Recognition with Global-Aware Fusion on Multi-scale Feature Representation	Apr 12, 2022	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available	1
MMER: Multimodal Multi-task Learning for Speech Emotion Recognition	Mar 31, 2022	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	1
Speech Emotion Recognition with Co-Attention based Multi-level Acoustic Information	Mar 29, 2022	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available	1
SepTr: Separable Transformer for Audio Spectrogram Processing	Mar 17, 2022	Audio ClassificationSpeech Emotion Recognition	CodeCode Available	1
Semi-FedSER: Semi-supervised Learning for Speech Emotion Recognition On Federated Learning using Multiview Pseudo-Labeling	Mar 15, 2022	Emotion RecognitionFederated Learning	CodeCode Available	1
Privacy-preserving Speech Emotion Recognition through Semi-Supervised Federated Learning	Feb 5, 2022	Emotion RecognitionFederated Learning	CodeCode Available	1

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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