SOTAVerified

Emotion Classification

Emotion classification, or emotion categorization, is the task of recognising emotions to classify them into the corresponding category. Given an input, classify it as 'neutral or no emotion' or as one, or more, of several given emotions that best represent the mental state of the subject's facial expression, words, and so on. Some example benchmarks include ROCStories, Many Faces of Anger (MFA), and GoEmotions. Models can be evaluated using metrics such as the Concordance Correlation Coefficient (CCC) and the Mean Squared Error (MSE).

Papers

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Showing 401–425 of 458 papers

TitleStatusHype
Advanced LSTM: A Study about Better Time Dependency Modeling in Emotion Recognition—0
Real-time Convolutional Neural Networks for Emotion and Gender ClassificationCode0
Temporal Multimodal Fusion for Video Emotion Classification in the Wild—0
DMGroup at EmoInt-2017: Emotion Intensity Using Ensemble Method—0
UWat-Emote at EmoInt-2017: Emotion Intensity Detection using Affect Clues, Sentiment Polarity and Word Embeddings—0
deepCybErNet at EmoInt-2017: Deep Emotion Intensities in Tweets—0
MoodSwipe: A Soft Keyboard that Suggests MessageBased on User-Specified Emotions—0
A Question Answering Approach for Emotion Cause Extraction—0
A Question Answering Approach to Emotion Cause Extraction—0
EmoTxt: A Toolkit for Emotion Recognition from TextCode0
Multimodal Classification for Analysing Social Media—0
MoodSwipe: A Soft Keyboard that Suggests Messages Based on User-Specified Emotions—0
Emotion Recognition by Body Movement Representation on the Manifold of Symmetric Positive Definite Matrices—0
CNN based music emotion classification—0
Group Visual Sentiment Analysis—0
Towards Wide Learning: Experiments in HealthcareCode0
Corpus Fusion for Emotion Classification—0
Two-View Label Propagation to Semi-supervised Reader Emotion Classification—0
Selective Co-occurrences for Word-Emotion Association—0
Microblog Emotion Classification by Computing Similarity in Text, Time, and Space—0
Learning Multi-level Deep Representations for Image Emotion Classification—0
How Do I Look? Publicity Mining From Distributed Keyword Representation of Socially Infused News Articles—0
Emotion Distribution Learning from Texts—0
Minimax Filter: Learning to Preserve Privacy from Inference AttacksCode0
Event Based Emotion Classification for News Articles—0
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All datasetsCMU-MOSEISemEval 2018 Task 1E-cEWALKMFAROCStoriesArmanEmoCAER-DynamicRAVDESSShortPersianEmo

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MARLIN (ViT-L)Accuracy80.63—Unverified
2MARLIN (ViT-B)Accuracy80.6—Unverified
3MARLIN (ViT-S)Accuracy80.38—Unverified
4ConCluGenAccuracy66.48—Unverified
#ModelMetricClaimedVerifiedStatus
1SpanEmoAccuracy0.6—Unverified
2BERT+DKAccuracy0.59—Unverified
3BERT-GCNAccuracy0.59—Unverified
4Transformer (finetune)Macro-F10.56—Unverified
#ModelMetricClaimedVerifiedStatus
1ProxEmo (ours)Accuracy82.4—Unverified
2STEP [bhattacharya2019step]Accuracy78.24—Unverified
3Baseline (Vanilla LSTM) [Ewalk]Accuracy55.47—Unverified
#ModelMetricClaimedVerifiedStatus
1MLKNNF-F1 score (Comb.)0.34—Unverified
2CC - XGBF-F1 score (Comb.)0.33—Unverified
#ModelMetricClaimedVerifiedStatus
1Semi-supervisionF165.88—Unverified
2NPN + Explanation TrainingF130.29—Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.65—Unverified
#ModelMetricClaimedVerifiedStatus
1CAERNetAccuracy77.04—Unverified
#ModelMetricClaimedVerifiedStatus
1ERANN-0-4Top-1 Accuracy74.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.71—Unverified