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 1251–1275 of 2041 papers

TitleStatusHype
以遷移學習改善深度神經網路模型於中文歌詞情緒辨識 (Using Transfer Learning to Improve Deep Neural Networks for Lyrics Emotion Recognition in Chinese)—0
Classifying Emotional Utterances by Employing Multi-modal Speech Emotion Recognition—0
Retrofitting of Pre-trained Emotion Words with VAD-dimensions and the Plutchik Emotions—0
The Validity of Lexicon-based Sentiment Analysis in Interdisciplinary Research—0
Affect-DML: Context-Aware One-Shot Recognition of Human Affect using Deep Metric LearningCode0
Representation learning through cross-modal conditional teacher-student training for speech emotion recognition—0
A Case Study on the Independence of Speech Emotion Recognition in Bangla and English Languages using Language-Independent Prosodic Features—0
Structure-Preserving Graph Kernel for Brain Network Classification—0
Multimodal Emotion Recognition on RAVDESS Dataset Using Transfer Learning—0
Cross-cultural Emotion Classification: the Effect of Emotional Intensity and Acoustic Features—0
EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue Systems—0
Emotion analysis and detection during COVID-19—0
All in One: A Multi-Task Learning for Emoji, Sentiment and Emotion Analysis in Code-Mixed Text—0
Biologically inspired speech emotion recognition—0
Speech Emotion Recognition Using Deep Sparse Auto-Encoder Extreme Learning Machine with a New Weighting Scheme and Spectro-Temporal Features Along with Classical Feature Selection and A New Quantum-Inspired Dimension Reduction Method—0
Multilingual and Multilabel Emotion Recognition using Virtual Adversarial Training—0
Multimodal End-to-End Group Emotion Recognition using Cross-Modal Attention—0
Deep Convolution Network Based Emotion Analysis for Automatic Detection of Mild Cognitive Impairment in the Elderly—0
Grassmannian learning mutual subspace method for image set recognition—0
Leveraging Sentiment Analysis Knowledge to Solve Emotion Detection Tasks—0
Facial Emotion Recognition using Deep Residual Networks in Real-World Environments—0
A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding—0
Multi-Cue Adaptive Emotion Recognition Network—0
ML-PersRef: A Machine Learning-based Personalized Multimodal Fusion Approach for Referencing Outside Objects From a Moving VehicleCode0
Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations—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