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 371–380 of 431 papers

Title	Date	Tasks	Status
Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition	Jul 7, 2022	Cross-corpusDeep Reinforcement Learning	—Unverified
Domain Adversarial for Acoustic Emotion Recognition	Apr 20, 2018	AttributeEmotion Recognition	—Unverified
Double Multi-Head Attention Multimodal System for Odyssey 2024 Speech Emotion Recognition Challenge	Jun 15, 2024	Emotion RecognitionPosition	—Unverified
DSNet: Disentangled Siamese Network with Neutral Calibration for Speech Emotion Recognition	Dec 25, 2023	DisentanglementEmotion Recognition	—Unverified
Dynamic Layer Customization for Noise Robust Speech Emotion Recognition in Heterogeneous Condition Training	Oct 21, 2020	Domain AdaptationEmotion Recognition	—Unverified
標記對於類神經語音情緒辨識系統辨識效果之影響(Effects of Label in Neural Speech Emotion Recognition System)[In Chinese]	Oct 1, 2016	Emotion RecognitionSpeech Emotion Recognition	—Unverified
ED-TTS: Multi-Scale Emotion Modeling using Cross-Domain Emotion Diarization for Emotional Speech Synthesis	Jan 16, 2024	DenoisingEmotional Speech Synthesis	—Unverified
Effect of different splitting criteria on the performance of speech emotion recognition	Oct 26, 2022	Emotion RecognitionSentence	—Unverified
Emo-bias: A Large Scale Evaluation of Social Bias on Speech Emotion Recognition	Jun 7, 2024	Emotion RecognitionSelf-Supervised Learning	—Unverified
EMO-Codec: An In-Depth Look at Emotion Preservation capacity of Legacy and Neural Codec Models With Subjective and Objective Evaluations	Jul 22, 2024	Emotion RecognitionSpeech Emotion Recognition	—Unverified

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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