SOTAVerified

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 1251–1275 of 2041 papers

TitleStatusHype
Towards Machine Unlearning for Paralinguistic Speech Processing—0
Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning—0
Towards Practical Emotion Recognition: An Unsupervised Source-Free Approach for EEG Domain Adaptation—0
Towards Relatable Explainable AI with the Perceptual Process—0
Towards Robust Multimodal Physiological Foundation Models: Handling Arbitrary Missing Modalities—0
Towards Sentiment and Emotion aided Multi-modal Speech Act Classification in Twitter—0
Towards Speech Emotion Recognition "in the wild" using Aggregated Corpora and Deep Multi-Task Learning—0
Towards Subject Agnostic Affective Emotion Recognition—0
Towards Transferable Speech Emotion Representation: On loss functions for cross-lingual latent representations—0
Toward the application of XAI methods in EEG-based systems—0
Training and Profiling a Pediatric Emotion Recognition Classifier on Mobile Devices—0
Improved Digital Therapy for Developmental Pediatrics Using Domain-Specific Artificial Intelligence: Machine Learning Study—0
Training Deep Neural Networks with Different Datasets In-the-wild: The Emotion Recognition Paradigm—0
Training speech emotion classifier without categorical annotations—0
Transferable Positive/Negative Speech Emotion Recognition via Class-wise Adversarial Domain Adaptation—0
Transfer Learning for Personality Perception via Speech Emotion Recognition—0
Transformer-Based Self-Supervised Learning for Emotion Recognition—0
Transformer-based Self-supervised Multimodal Representation Learning for Wearable Emotion Recognition—0
Transforming the Embeddings: A Lightweight Technique for Speech Emotion Recognition Tasks—0
TRILLsson: Distilled Universal Paralinguistic Speech Representations—0
TRNet: Two-level Refinement Network leveraging Speech Enhancement for Noise Robust Speech Emotion Recognition—0
TrueHappiness: Neuromorphic Emotion Recognition on TrueNorth—0
Turbo your multi-modal classification with contrastive learning—0
Tweeting AI: Perceptions of Lay vs Expert Twitterati—0
Two in One Go: Single-stage Emotion Recognition with Decoupled Subject-context Transformer—0
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All datasetsEmomusicRAVDESSEMOTICFER2013MaSaC_ERCMPEDMSP-PodcastSEEDคลิปคุณพ่อให้ลูกสาวยืมโทรศัพท์และความสนุกสนาน

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1M2D-CLAPEmoA77.4—Unverified
2M2D2EmoA76.7—Unverified
3M2DEmoA76.1—Unverified
4Jukebox (Pre-training: CALM)EmoA72.1—Unverified
5CLMR (Pre-training: contrastive)EmoA67.8—Unverified
#ModelMetricClaimedVerifiedStatus
1LogisticRegression on posteriors of xlsr-Wav2Vec2.0&bi-LSTM+AttentionAccuracy86.7—Unverified
2MultiMAE-DERWAR83.61—Unverified
3Intermediate-Attention-FusionAccuracy81.58—Unverified
4Logistic Regression on posteriors of the CNN-14&biLSTM-GuidedSTAccuracy80.08—Unverified
5ERANN-0-4Accuracy74.8—Unverified
#ModelMetricClaimedVerifiedStatus
1CAGETop-3 Accuracy (%)14.73—Unverified
2FocusCLIPTop-3 Accuracy (%)13.73—Unverified
#ModelMetricClaimedVerifiedStatus
1VGG based5-class test accuracy66.13—Unverified
#ModelMetricClaimedVerifiedStatus
1MaSaC-ERC-ZF1-score (Weighted)51.17—Unverified
#ModelMetricClaimedVerifiedStatus
1BiHDMAccuracy40.34—Unverified
#ModelMetricClaimedVerifiedStatus
1w2v2-L-robust-12Concordance correlation coefficient (CCC)0.64—Unverified
#ModelMetricClaimedVerifiedStatus
14D-aNNAccuracy96.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN1'"1—Unverified