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Beyond Emotion Labels: Multimodal AI Approaches to Affective Computing and Sentiment Modeling

https://doi.org/10.2139/ssrn.6890916
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EmoBone: A Multinational Audio Dataset of Emotional Bone Conducted Speech
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MEAD: A Large-Scale Audio-Visual Dataset for Emotional Talking-Face Generation
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Exploring the Ethical Dimensions and Societal Consequences of Affective Computing
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Saliency-Guided Emotion Modeling: Predicting Viewer Reactions from Video Stimuli
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A review on EEG-based multimodal learning for emotion recognition
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IEMOCAP: interactive emotional dyadic motion capture database
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Federated learning inspired privacy sensitive emotion recognition based on multi-modal physiological sensors
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Multimodal sentiment analysis using image and text fusion for emotion detection
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Saliency map and deep learning based efficient facial emotion recognition technique for facial images
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Survey of deep emotion recognition in dynamic data using facial, speech and textual cues
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Deep Affect Prediction in-the-Wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond
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Domain adaptation for bias mitigation in affective computing: use cases for facial emotion recognition and sentiment analysis systems
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Speech emotion recognition using deep 1D & 2D CNN LSTM networks
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Invisible algorithms, visible outcomes: Roles of emotional labor and work gamification in gigs
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Wearable electroencephalography and multi-modal mental state classification: A systematic literature review
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The cultural construction of emotions
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A survey of multimodal sentiment analysis
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A review of affective computing: From unimodal analysis to multimodal fusion
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Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
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A systematic review on affective computing: emotion models, databases, and recent advances
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Emotion recognition from unimodal to multimodal analysis: A review
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Deep visual domain adaptation: A survey
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Context-based emotion recognition: A survey
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Dynamic label correlations and dual-semantic enhancement learning for cross-modal retrieval
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Challenges in real-life emotion annotation and machine learning based detection
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Challenges in representation learning: A report on three machine learning contests
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Natural language processing applications for low-resource languages
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Distinctive Image Features from Scale-Invariant Keypoints
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Facial expression and emotion.
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On the universality and cultural specificity of emotion recognition: A meta-analysis.
inferredcites →https://doi.org/10.1037/0033-295x.110.1.145openalex-snapshot
Core affect and the psychological construction of emotion.
inferredcites →https://doi.org/10.1038/s41562-022-01505-5openalex-snapshot
Modelling individual and cross-cultural variation in the mapping of emotions to speech prosody
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A Multimodal Dataset for Mixed Emotion Recognition
inferredcites →https://doi.org/10.1038/s41598-024-55371-4openalex-snapshot
Affective super-traits and/or individual patterns: a variable-centered and a person-centered approach of primary emotional aspects of personality
inferredcites →https://doi.org/10.1038/s41598-024-72432-wopenalex-snapshot
Culture shapes how we describe facial expressions
inferredcites →https://doi.org/10.1038/s41598-024-76968-9openalex-snapshot
Decoding viewer emotions in video ads
inferredcites →https://doi.org/10.1073/pnas.1200155109openalex-snapshot
Facial expressions of emotion are not culturally universal
inferredcites →https://doi.org/10.1093/scan/nsx060openalex-snapshot
The theory of constructed emotion: an active inference account of interoception and categorization
inferredcites →https://doi.org/10.1109/access.2024.3422480openalex-snapshot
A Comprehensive Survey on Affective Computing: Challenges, Trends, Applications, and Future Directions
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A Systematic Review on Multimodal Emotion Recognition: Building Blocks, Current State, Applications, and Challenges
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.502openalex-snapshot
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
inferredcites →https://doi.org/10.1109/cvpr.2019.00453openalex-snapshot
A Style-Based Generator Architecture for Generative Adversarial Networks
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00561openalex-snapshot
Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causality
inferredcites →https://doi.org/10.1109/cvpr52733.2024.01219openalex-snapshot
MART: Masked Affective RepresenTation Learning via Masked Temporal Distribution Distillation
inferredcites →https://doi.org/10.1109/cvprw.2016.182openalex-snapshot
Extended DISFA Dataset: Investigating Posed and Spontaneous Facial Expressions
inferredcites →https://doi.org/10.1109/cvprw56347.2022.00259openalex-snapshot
ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challenges
inferredcites →https://doi.org/10.1109/cvprw67362.2025.00568openalex-snapshot
Interactive Multimodal Framework with Temporal Modeling for Emotion Recognition
inferredcites →https://doi.org/10.1109/icassp.2016.7472669openalex-snapshot
Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network
inferredcites →https://doi.org/10.1109/icassp40776.2020.9053762openalex-snapshot
Multimodal Transformer Fusion for Continuous Emotion Recognition
inferredcites →https://doi.org/10.1109/iccst53801.2021.00027openalex-snapshot
Multimodal Emotion Recognition in Deep Learning:a Survey
inferredcites →https://doi.org/10.1109/iccv51070.2023.01864openalex-snapshot
EmoSet: A Large-scale Visual Emotion Dataset with Rich Attributes
inferredcites →https://doi.org/10.1109/iccvw.2017.45openalex-snapshot
Cross-Media Learning for Image Sentiment Analysis in the Wild
inferredcites →https://doi.org/10.1109/jbhi.2024.3416944openalex-snapshot
Graph Convolutional Network With Connectivity Uncertainty for EEG-Based Emotion Recognition
inferredcites →https://doi.org/10.1109/jstsp.2022.3188113openalex-snapshot
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
inferredcites →https://doi.org/10.1109/mmul.2012.26openalex-snapshot
Collecting Large, Richly Annotated Facial-Expression Databases from Movies
inferredcites →https://doi.org/10.1109/msp.2020.2975749openalex-snapshot
Federated Learning: Challenges, Methods, and Future Directions
inferredcites →https://doi.org/10.1109/t-affc.2010.1openalex-snapshot
Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications
inferredcites →https://doi.org/10.1109/taffc.2014.2336244openalex-snapshot
CREMA-D: Crowd-Sourced Emotional Multimodal Actors Dataset
inferredcites →https://doi.org/10.1109/taffc.2017.2736999openalex-snapshot
Building Naturalistic Emotionally Balanced Speech Corpus by Retrieving Emotional Speech from Existing Podcast Recordings
inferredcites →https://doi.org/10.1109/taffc.2017.2740923openalex-snapshot
AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild
inferredcites →https://doi.org/10.1109/taffc.2020.2981446openalex-snapshot
Deep Facial Expression Recognition: A Survey
inferredcites →https://doi.org/10.1109/taffc.2024.3354382openalex-snapshot
A Multi-Level Alignment and Cross-Modal Unified Semantic Graph Refinement Network for Conversational Emotion Recognition
inferredcites →https://doi.org/10.1109/taffc.2024.3367371openalex-snapshot
Continuous Emotion Ambiguity Prediction: Modeling With Beta Distributions
inferredcites →https://doi.org/10.1109/taffc.2025.3584775openalex-snapshot
Rethinking Emotion Annotations in the Era of Large Language Models
inferredcites →https://doi.org/10.1109/taffc.2025.3621086openalex-snapshot
Lightweight Multimodal Emotion Recognition for Companion Robots: A Deep Learning Framework Integrating Facial and Speech Features
inferredcites →https://doi.org/10.1109/taffc.2025.3624354openalex-snapshot
A Comprehensive Survey on Datasets for Affective Computing and Mental Disorder
inferredcites →https://doi.org/10.1109/tai.2024.3445325openalex-snapshot
Deep Imbalanced Learning for Multimodal Emotion Recognition in Conversations
inferredcites →https://doi.org/10.1109/taslp.2021.3122291openalex-snapshot
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units
inferredcites →https://doi.org/10.1109/tbiom.2025.3601217openalex-snapshot
Review of Demographic Fairness in Face Recognition
inferredcites →https://doi.org/10.1109/tip.2017.2655445openalex-snapshot
Data-Dependent Label Distribution Learning for Age Estimation
inferredcites →https://doi.org/10.1109/tip.2021.3118983openalex-snapshot
SOLVER: Scene-Object Interrelated Visual Emotion Reasoning Network
inferredcites →https://doi.org/10.1109/tmm.2015.2404779openalex-snapshot
Learning Spatial and Temporal Extents of Human Actions for Action Detection
inferredcites →https://doi.org/10.1109/tmm.2018.2803520openalex-snapshot
Visual Sentiment Prediction Based on Automatic Discovery of Affective Regions
inferredcites →https://doi.org/10.1109/tmm.2019.2939744openalex-snapshot
WSCNet: Weakly Supervised Coupled Networks for Visual Sentiment Classification and Detection
inferredcites →https://doi.org/10.1109/tpami.2002.1017623openalex-snapshot
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
inferredcites →https://doi.org/10.1109/tpami.2016.2599174openalex-snapshot
Long-Term Recurrent Convolutional Networks for Visual Recognition and Description
inferredcites →https://doi.org/10.1109/tpami.2018.2798607openalex-snapshot
Multimodal Machine Learning: A Survey and Taxonomy
inferredcites →https://doi.org/10.1109/tpami.2024.3361979openalex-snapshot
Metrics for Dataset Demographic Bias: A Case Study on Facial Expression Recognition
inferredcites →https://doi.org/10.1109/tpami.2024.3443129openalex-snapshot
Towards Context-Aware Emotion Recognition Debiasing From a Causal Demystification Perspective via De-Confounded Training
inferredcites →https://doi.org/10.1109/tts.2021.3111823openalex-snapshot
A Comprehensive Study on Face Recognition Biases Beyond Demographics
inferredcites →https://doi.org/10.1145/1873951.1873965openalex-snapshot
Affective image classification using features inspired by psychology and art theory
inferredcites →https://doi.org/10.1145/1873951.1874060openalex-snapshot
Analyzing and predicting sentiment of images on the social web
inferredcites →https://doi.org/10.1145/2502081.2502282openalex-snapshot
Large-scale visual sentiment ontology and detectors using adjective noun pairs
inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot
Deep Learning with Differential Privacy
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3323873.3326593openalex-snapshot
Image Emotion Distribution Learning with Graph Convolutional Networks
inferredcites →https://doi.org/10.1145/3347320.3357690openalex-snapshot
Efficient Spatial Temporal Convolutional Features for Audiovisual Continuous Affect Recognition
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From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI
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Technical Solutions to Emotion AI's Privacy Harms: A Systematic Literature Review
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Long Short-Term Memory
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MissModal: Increasing Robustness to Missing Modality in Multimodal Sentiment Analysis
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Context in Emotion Perception
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Visual Listening In: Extracting Brand Image Portrayed on Social Media
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Found in Translation: Learning Robust Joint Representations by Cyclic Translations between Modalities
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SMIL: Multimodal Learning with Severely Missing Modality
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SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and Arabic
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Layer-wise Fusion with Modality Independence Modeling for Multi-modal Emotion Recognition
inferredcites →https://doi.org/10.18653/v1/2024.acl-long.114openalex-snapshot
Handling Ambiguity in Emotion: From Out-of-Domain Detection to Distribution Estimation
inferredcites →https://doi.org/10.18653/v1/2025.acl-long.925openalex-snapshot
CULEMO: Cultural Lenses on Emotion - Benchmarking LLMs for Cross-Cultural Emotion Understanding
inferredcites →https://doi.org/10.18653/v1/d17-1115openalex-snapshot
Tensor Fusion Network for Multimodal Sentiment Analysis
inferredcites →https://doi.org/10.18653/v1/p18-1208openalex-snapshot
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph
inferredcites →https://doi.org/10.18653/v1/p19-1050openalex-snapshot
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
inferredcites →https://doi.org/10.18653/v1/p19-1455openalex-snapshot
Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)
inferredcites →https://doi.org/10.18653/v1/p19-1656openalex-snapshot
Multimodal Transformer for Unaligned Multimodal Language Sequences
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Surveillance in the Workplace: Past, Present, and Future
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Glove: Global Vectors for Word Representation
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An Overview of Heart Rate Variability Metrics and Norms
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Efficient Dynamic Emotion Recognition from Facial Expressions Using Statistical Spatio-Temporal Geometric Features
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From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications
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Machine Learning Interpretability: A Survey on Methods and Metrics
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Transforming Data Annotation with AI Agents: A Review of Architectures, Reasoning, Applications, and Impact
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Context_Driven Emotion Recognition: Integrating Multi_Cue Fusion and Attention Mechanisms for Enhanced Accuracy on the NCAER_S Dataset
inferredcites →https://doi.org/10.3390/psycholint7020043openalex-snapshot
Ethical Considerations in Emotion Recognition Research
inferredcites →https://doi.org/10.3758/bf03192732openalex-snapshot
Emotional category data on images from the international affective picture system
inferredcites →https://doi.org/10.4018/jse.2010101605openalex-snapshot
Automatic, Dimensional and Continuous Emotion Recognition
inferredcites →https://doi.org/10.7717/peerj-cs.2649openalex-snapshot
Improved BCI calibration in multimodal emotion recognition using heterogeneous adversarial transfer learning
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