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 1451–1475 of 2041 papers

TitleStatusHype
Joint Deep Cross-Domain Transfer Learning for Emotion Recognition—0
Joint Emotion Analysis via Multi-task Gaussian Processes—0
Joint Emotion Label Space Modelling for Affect Lexica—0
Joint Learning for Emotion Classification and Emotion Cause Detection—0
JudithJeyafreedaAndrew@TamilNLP-ACL2022:CNN for Emotion Analysis in Tamil—0
KEVER^2: Knowledge-Enhanced Visual Emotion Reasoning and Retrieval—0
Fine-grained Early Frequency Attention for Deep Speaker Representation Learning—0
Knowledge-Aligned Counterfactual-Enhancement Diffusion Perception for Unsupervised Cross-Domain Visual Emotion Recognition—0
Knowledge-aware Bayesian Co-attention for Multimodal Emotion Recognition—0
Knowledge Aware Emotion Recognition in Textual Conversations via Multi-Task Incremental Transformer—0
Knowledge-Interactive Network with Sentiment Polarity Intensity-Aware Multi-Task Learning for Emotion Recognition in Conversations—0
Korean Drama Scene Transcript Dataset for Emotion Recognition in Conversations—0
Korean Twitter Emotion Classification Using Automatically Built Emotion Lexicons and Fine-Grained Features—0
KSU at SemEval-2019 Task 3: Hybrid Features for Emotion Recognition in Textual Conversation—0
Label-less Learning for Traffic Control in an Edge Network—0
Ladder Networks for Emotion Recognition: Using Unsupervised Auxiliary Tasks to Improve Predictions of Emotional Attributes—0
LanSER: Language-Model Supported Speech Emotion Recognition—0
Large Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition—0
Large Vision-Language Models as Emotion Recognizers in Context Awareness—0
Layer-Wise Analysis of Self-Supervised Acoustic Word Embeddings: A Study on Speech Emotion Recognition—0
LDEB -- Label Digitization with Emotion Binarization and Machine Learning for Emotion Recognition in Conversational Dialogues—0
LEAPMood: Light and Efficient Architecture to Predict Mood with Genetic Algorithm driven Hyperparameter Tuning—0
Learning a Facial Expression Embedding Disentangled From Identity—0
Learning Affective Correspondence between Music and Image—0
Learning Annotation Consensus for Continuous Emotion Recognition—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