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 51–75 of 2041 papers

TitleStatusHype
Distribution-based Emotion Recognition in ConversationCode1
Cross Attentional Audio-Visual Fusion for Dimensional Emotion RecognitionCode1
Cross-Lingual Cross-Age Group Adaptation for Low-Resource Elderly Speech Emotion RecognitionCode1
A cross-modal fusion network based on self-attention and residual structure for multimodal emotion recognitionCode1
Accuracy enhancement method for speech emotion recognition from spectrogram using temporal frequency correlation and positional information learning through knowledge transferCode1
Affective Behaviour Analysis Using Pretrained Model with Facial PrioriCode1
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal NuancesCode1
Cross Task Neural Architecture Search for EEG Signal ClassificationsCode1
DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in ConversationsCode1
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in ConversationCode1
DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionCode1
Directed Acyclic Graph Network for Conversational Emotion RecognitionCode1
Contrast and Generation Make BART a Good Dialogue Emotion RecognizerCode1
Continuous Emotion Recognition using Visual-audio-linguistic information: A Technical Report for ABAW3Code1
Conversation Understanding using Relational Temporal Graph Neural Networks with Auxiliary Cross-Modality InteractionCode1
Context De-confounded Emotion RecognitionCode1
A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party ConversationsCode1
Contextual Information and Commonsense Based Prompt for Emotion Recognition in ConversationCode1
Cooperative Sentiment Agents for Multimodal Sentiment AnalysisCode1
Crowdsourced and Automatic Speech Prominence EstimationCode1
Do Music Generation Models Encode Music Theory?Code1
COGMEN: COntextualized GNN based Multimodal Emotion recognitioNCode1
Codified audio language modeling learns useful representations for music information retrievalCode1
Compact Graph Architecture for Speech Emotion RecognitionCode1
Cluster-Level Contrastive Learning for Emotion Recognition in ConversationsCode1
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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