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 626–650 of 2041 papers

TitleStatusHype
Towards Subject Agnostic Affective Emotion Recognition—0
SALMONN: Towards Generic Hearing Abilities for Large Language ModelsCode3
From Multilingual Complexity to Emotional Clarity: Leveraging Commonsense to Unveil Emotions in Code-Mixed DialoguesCode0
EmoDiarize: Speaker Diarization and Emotion Identification from Speech Signals using Convolutional Neural Networks—0
CLARA: Multilingual Contrastive Learning for Audio Representation AcquisitionCode1
Bias in Emotion Recognition with ChatGPT—0
DialogueLLM: Context and Emotion Knowledge-Tuned Large Language Models for Emotion Recognition in ConversationsCode1
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference—0
Crowdsourced and Automatic Speech Prominence EstimationCode1
Hypercomplex Multimodal Emotion Recognition from EEG and Peripheral Physiological SignalsCode1
Towards Emotion-Based Synthetic Consciousness: Using LLMs to Estimate Emotion Probability Vectors—0
Integrating Contrastive Learning into a Multitask Transformer Model for Effective Domain Adaptation—0
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPTCode2
Acoustic and linguistic representations for speech continuous emotion recognition in call center conversations—0
In the Blink of an Eye: Event-based Emotion RecognitionCode1
Towards A Robust Group-level Emotion Recognition via Uncertainty-Aware Learning—0
Multimodal Prompt Transformer with Hybrid Contrastive Learning for Emotion Recognition in Conversation—0
Prompting Audios Using Acoustic Properties For Emotion Representation—0
Graph Neural Network-based EEG Classification: A Survey—0
End-to-End Continuous Speech Emotion Recognition in Real-life Customer Service Call Center Conversations—0
Active Learning Based Fine-Tuning Framework for Speech Emotion Recognition—0
Sarcasm in Sight and Sound: Benchmarking and Expansion to Improve Multimodal Sarcasm Detection—0
MONOVAB : An Annotated Corpus for Bangla Multi-label Emotion DetectionCode0
Unsupervised Representations Improve Supervised Learning in Speech Emotion Recognition—0
Learning Noise-Robust Joint Representation for Multimodal Emotion Recognition under Incomplete Data ScenariosCode0
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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