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 1801–1825 of 2041 papers

TitleStatusHype
A Novel Geometric Framework on Gram Matrix Trajectories for Human Behavior Understanding—0
It All Matters: Reporting Accuracy, Inference Time and Power Consumption for Face Emotion Recognition on Embedded Systems—0
Evaluating Gammatone Frequency Cepstral Coefficients with Neural Networks for Emotion Recognition from SpeechCode0
On Enhancing Speech Emotion Recognition using Generative Adversarial Networks—0
Multimodal Relational Tensor Network for Sentiment and Emotion Classification—0
Adversarial Auto-encoders for Speech Based Emotion Recognition—0
Attention Based Fully Convolutional Network for Speech Emotion RecognitionCode0
DNN-HMM based Speaker Adaptive Emotion Recognition using Proposed Epoch and MFCC Features—0
EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNet—0
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos—0
CrystalFeel at SemEval-2018 Task 1: Understanding and Detecting Emotion Intensity using Affective Lexicons—0
EmoIntens Tracker at SemEval-2018 Task 1: Emotional Intensity Levels in \#Tweets—0
Mutux at SemEval-2018 Task 1: Exploring Impacts of Context Information On Emotion Detection—0
Enabling Deep Learning of Emotion With First-Person Seed Expressions—0
EMA at SemEval-2018 Task 1: Emotion Mining for Arabic—0
SemEval 2018 Task 2: Multilingual Emoji Prediction—0
SINAI at SemEval-2018 Task 1: Emotion Recognition in Tweets—0
psyML at SemEval-2018 Task 1: Transfer Learning for Sentiment and Emotion Analysis—0
IIT Delhi at SemEval-2018 Task 1 : Emotion Intensity Prediction—0
Frustrated, Polite, or Formal: Quantifying Feelings and Tone in Email—0
3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children With Autism—0
LT3 at SemEval-2018 Task 1: A classifier chain to detect emotions in tweets—0
Efficient Low-rank Multimodal Fusion with Modality-Specific FactorsCode0
Context-aware Cascade Attention-based RNN for Video Emotion Recognition—0
Curriculum Learning for Speech Emotion Recognition from Crowdsourced Labels—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