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 1876–1900 of 2041 papers

TitleStatusHype
EEG Emotion Copilot: Optimizing Lightweight LLMs for Emotional EEG Interpretation with Assisted Medical Record GenerationCode0
Label Uncertainty Modeling and Prediction for Speech Emotion Recognition using t-DistributionsCode0
Dynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in ConversationCode0
ResEmoteNet: Bridging Accuracy and Loss Reduction in Facial Emotion RecognitionCode0
Filter-based multi-task cross-corpus feature learning for speech emotion recognitionCode0
Speech-based emotion recognition with self-supervised models using attentive channel-wise correlations and label smoothingCode0
Large Language Models Meet Contrastive Learning: Zero-Shot Emotion Recognition Across LanguagesCode0
FerNeXt: Facial Expression Recognition Using ConvNeXt with Channel AttentionCode0
Context-Dependent Sentiment Analysis in User-Generated VideosCode0
FeedForward at SemEval-2024 Task 10: Trigger and sentext-height enriched emotion analysis in multi-party conversationsCode0
FedMultimodal: A Benchmark For Multimodal Federated LearningCode0
DSC IIT-ISM at SemEval-2020 Task 8: Bi-Fusion Techniques for Deep Meme Emotion AnalysisCode0
SpeechCaps: Advancing Instruction-Based Universal Speech Models with Multi-Talker Speaking Style CaptioningCode0
Context-Dependent Embedding Utterance Representations for Emotion Recognition in ConversationsCode0
Multi-modal Speech Emotion Recognition via Feature Distribution Adaptation NetworkCode0
A Weakly Supervised Dataset of Fine-Grained Emotions in PortugueseCode0
An Emotion Recognition Embedded System using a Lightweight Deep Learning ModelCode0
Learning Alignment for Multimodal Emotion Recognition from SpeechCode0
Feature-Based Dual Visual Feature Extraction Model for Compound Multimodal Emotion RecognitionCode0
Authentic Emotion Mapping: Benchmarking Facial Expressions in Real NewsCode0
Revise, Reason, and Recognize: LLM-Based Emotion Recognition via Emotion-Specific Prompts and ASR Error CorrectionCode0
Unveiling Hidden Factors: Explainable AI for Feature Boosting in Speech Emotion RecognitionCode0
TRANSFER :- DEEP INDUCTIVE NETWORK FOR FACIAL EMOTION RECOGNITIONCode0
An audiovisual and contextual approach for categorical and continuous emotion recognition in-the-wildCode0
NAC-TCN: Temporal Convolutional Networks with Causal Dilated Neighborhood Attention for Emotion UnderstandingCode0
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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