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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1801–1850 of 2041 papers

TitleStatusHype
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
3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children With Autism—0
Frustrated, Polite, or Formal: Quantifying Feelings and Tone in Email—0
Enabling Deep Learning of Emotion With First-Person Seed Expressions—0
IIT Delhi at SemEval-2018 Task 1 : Emotion Intensity Prediction—0
Mutux at SemEval-2018 Task 1: Exploring Impacts of Context Information On Emotion Detection—0
psyML at SemEval-2018 Task 1: Transfer Learning for Sentiment and Emotion Analysis—0
EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNet—0
SINAI at SemEval-2018 Task 1: Emotion Recognition in Tweets—0
EMA at SemEval-2018 Task 1: Emotion Mining for Arabic—0
LT3 at SemEval-2018 Task 1: A classifier chain to detect emotions in tweets—0
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos—0
EmoIntens Tracker at SemEval-2018 Task 1: Emotional Intensity Levels in \#Tweets—0
SemEval 2018 Task 2: Multilingual Emoji Prediction—0
CrystalFeel at SemEval-2018 Task 1: Understanding and Detecting Emotion Intensity using Affective Lexicons—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
Meta Transfer Learning for Facial Emotion Recognition—0
ASR-based Features for Emotion Recognition: A Transfer Learning Approach—0
Convolutional Attention Networks for Multimodal Emotion Recognition from Speech and Text Data—0
Framewise approach in multimodal emotion recognition in OMG challenge—0
audEERING's approach to the One-Minute-Gradual Emotion Challenge—0
Dimensional emotion recognition using visual and textual cues—0
Multimodal Emotion Recognition for One-Minute-Gradual Emotion Challenge—0
A Multi-component CNN-RNN Approach for Dimensional Emotion Recognition in-the-wild—0
Transformer for Emotion RecognitionCode0
Multimodal Utterance-level Affect Analysis using Visual, Audio and Text FeaturesCode0
Classifier-based Polarity Propagation in a WordNet—0
A Vietnamese Dialog Act Corpus Based on ISO 24617-2 standard—0
EMTC: Multilabel Corpus in Movie Domain for Emotion Analysis in Conversational Text—0
Construction of English-French Multimodal Affective Conversational Corpus from TV Dramas—0
Contextual Dependencies in Time-Continuous Multidimensional Affect Recognition—0
Sentence and Clause Level Emotion Annotation, Detection, and Classification in a Multi-Genre Corpus—0
Understanding Emotions: A Dataset of Tweets to Study Interactions between Affect Categories—0
A Comparison Of Emotion Annotation Schemes And A New Annotated Data Set—0
WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art—0
Word Affect Intensities—0
Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and BeyondCode0
Ladder Networks for Emotion Recognition: Using Unsupervised Auxiliary Tasks to Improve Predictions of Emotional Attributes—0
DeepEmo: Learning and Enriching Pattern-Based Emotion RepresentationsCode0
Siamese Generative Adversarial Privatizer for Biometric Data—0
I Know How You Feel: Emotion Recognition with Facial Landmarks—0
Domain Adversarial for Acoustic Emotion Recognition—0
Multi-Modal Emotion recognition on IEMOCAP Dataset using Deep LearningCode0
On the Robustness of Speech Emotion Recognition for Human-Robot Interaction with Deep Neural Networks—0
Show:102550
← PrevPage 37 of 41Next →
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