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 1141–1150 of 2041 papers

Title	Date	Tasks	Status
Spatiotemporal Networks for Video Emotion Recognition	Apr 3, 2017	ClassificationEmotion Recognition	—Unverified
Speaker Attentive Speech Emotion Recognition	Apr 15, 2021	Emotion RecognitionSpeech Emotion Recognition	—Unverified
Speaker Characterization by means of Attention Pooling	May 7, 2024	Emotion RecognitionSpeaker Recognition	—Unverified
Speaker Emotion Recognition: Leveraging Self-Supervised Models for Feature Extraction Using Wav2Vec2 and HuBERT	Nov 5, 2024	Emotion Recognition	—Unverified
Speaker-Guided Encoder-Decoder Framework for Emotion Recognition in Conversation	Jun 7, 2022	DecoderEmotion Recognition	—Unverified
Speaker-invariant Affective Representation Learning via Adversarial Training	Nov 4, 2019	Emotion ClassificationEmotion Recognition	—Unverified
Speaker Normalization for Self-supervised Speech Emotion Recognition	Feb 2, 2022	Emotion RecognitionSpeech Emotion Recognition	—Unverified
Speech and Text-Based Emotion Recognizer	Dec 10, 2023	Data AugmentationEmotion Recognition	—Unverified
Speech-Based Emotion Recognition: Feature Selection by Self-Adaptive Multi-Criteria Genetic Algorithm	May 1, 2014	Emotion Recognitionfeature selection	—Unverified
Speech-Emotion Detection in an Indonesian Movie	May 1, 2020	Emotion RecognitionGeneral Classification	—Unverified

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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