Papers Emotion Classification
“Emotion Classification” 태그가 달린 논문 540편 · 필터 해제
AI-Driven Modular Services for Accessible Multilingual Education in Immersive Extended Reality Settings: Integrating Speech Processing, Translation, and Sign Language Rendering
This work introduces a modular platform that brings together six AI services, automatic speech recognition via OpenAI Whisper, multilingual translation through Meta NLLB, speech synthesis using AWS Polly, emotion classif…
Emotion ClassificationSpeech RecognitionSpeech SynthesisINTERACT: An AI-Driven Extended Reality Framework for Accesible Communication Featuring Real-Time Sign Language Interpretation and Emotion Recognition
Video conferencing has become central to professional collaboration, yet most platforms offer limited support for deaf, hard-of-hearing, and multilingual users. The World Health Organisation estimates that over 430 milli…
Emotion ClassificationEmotion RecognitionSpeech RecognitionVariational Encoder--Multi-Decoder (VE-MD) for Privacy-by-functional-design (Group) Emotion Recognition
Group Emotion Recognition (GER) aims to infer collective affect in social environments such as classrooms, crowds, and public events. Many existing approaches rely on explicit individual-level processing, including cropp…
Representation LearningEmotion ClassificationEmotion RecognitionMore Human, More Efficient: Aligning Annotations with Quantized SLMs
As Large Language Model (LLM) capabilities advance, the demand for high-quality annotation of exponentially increasing text corpora has outpaced human capacity, leading to the widespread adoption of LLMs in automatic eva…
Emotion ClassificationA Backbone Benchmarking Study on Self-supervised Learning as a Auxiliary Task with Texture-based Local Descriptors for Face Analysis
In this work, we benchmark with different backbones and study their impact for self-supervised learning (SSL) as an auxiliary task to blend texture-based local descriptors into feature modelling for efficient face analys…
Self-Supervised LearningRepresentation LearningEmotion ClassificationDeepFake DetectionDynamic Fusion-Aware Graph Convolutional Neural Network for Multimodal Emotion Recognition in Conversations
Multimodal emotion recognition in conversations (MERC) aims to identify and understand the emotions expressed by speakers during utterance interaction from multiple modalities (e.g., text, audio, images, etc.). Existing …
Multimodal Emotion RecognitionEmotion ClassificationCMHL: Contrastive Multi-Head Learning for Emotionally Consistent Text Classification
Textual Emotion Classification (TEC) is one of the most difficult NLP tasks. State of the art approaches rely on Large language models (LLMs) and multi-model ensembles. In this study, we challenge the assumption that lar…
Emotion ClassificationDomain GeneralizationMulti-Task LearningText ClassificationBTZSC: A Benchmark for Zero-Shot Text Classification Across Cross-Encoders, Embedding Models, Rerankers and LLMs
Zero-shot text classification (ZSC) offers the promise of eliminating costly task-specific annotation by matching texts directly to human-readable label descriptions. While early approaches have predominantly relied on c…
Natural Language InferenceEmotion ClassificationText ClassificationEmotion is Not Just a Label: Latent Emotional Factors in LLM Processing
Large language models are routinely deployed on text that varies widely in emotional tone, yet their reasoning behavior is typically evaluated without accounting for emotion as a source of representational variation. Pri…
Emotion ClassificationReading ComprehensionSentiment AnalysisWhat Do AI Agents Talk About? Discourse and Architectural Constraints in the First AI-Only Social Network
Moltbook is the first large-scale social network built for autonomous AI agent-to-agent interaction. Early studies on Moltbook have interpreted its agent discourse as evidence of peer learning and emergent social behavio…
Emotion ClassificationSpectroFusion-ViT: A Lightweight Transformer for Speech Emotion Recognition Using Harmonic Mel-Chroma Fusion
Speech is a natural means of conveying emotions, making it an effective method for understanding and representing human feelings. Reliable speech emotion recognition (SER) is central to applications in human-computer int…
Speech Emotion RecognitionEmotion ClassificationTransfer LearningPhysics-based phenomenological characterization of cross-modal bias in multimodal models
The term 'algorithmic fairness' is used to evaluate whether AI models operate fairly in both comparative (where fairness is understood as formal equality, such as "treat like cases as like") and non-comparative (where un…
Emotion ClassificationColor-based Emotion Representation for Speech Emotion Recognition
Speech emotion recognition (SER) has traditionally relied on categorical or dimensional labels. However, this technique is limited in representing both the diversity and interpretability of emotions. To overcome this lim…
Speech Emotion RecognitionEmotion ClassificationCircuit Fingerprints: How Answer Tokens Encode Their Geometrical Path
Circuit discovery and activation steering in transformers have developed as separate research threads, yet both operate on the same representational space. Are they two views of the same underlying structure? We show the…
Emotion ClassificationViGoEmotions: A Benchmark Dataset For Fine-grained Emotion Detection on Vietnamese Texts
Emotion classification plays a significant role in emotion prediction and harmful content detection. Recent advancements in NLP, particularly through large language models (LLMs), have greatly improved outcomes in this f…
Emotion ClassificationLexical NormalizationDAH-Net: A Dual-Attention Hybrid Network for Interpretable and Robust EEG-Based Emotion Recognition
EEG-based emotion recognition supports affective brain-computer interfaces and mental health monitoring yet remains challenged by signal complexity, subject variability, and limited interpretability. We propose DAH-Net, …
Emotion ClassificationEmotion RecognitionReasoning under Ambiguity: Uncertainty-Aware Multilingual Emotion Classification under Partial Supervision
Contemporary knowledge-based systems increasingly rely on multilingual emotion identification to support intelligent decision-making, yet they face major challenges due to emotional ambiguity and incomplete supervision. …
Emotion ClassificationEmotion RecognitionVideo-based Music Generation
As the volume of video content on the internet grows rapidly, finding a suitable soundtrack remains a significant challenge. This thesis presents EMSYNC (EMotion and SYNChronization), a fast, free, and automatic solution…
Emotion ClassificationMusic GenerationEmoAra: Emotion-Preserving English Speech Transcription and Cross-Lingual Translation with Arabic Text-to-Speech
This work presents EmoAra, an end-to-end emotion-preserving pipeline for cross-lingual spoken communication, motivated by banking customer service where emotional context affects service quality. EmoAra integrates Speech…
Speech Emotion RecognitionEmotion ClassificationMachine TranslationSpeech RecognitionThree-Way Emotion Classification of EEG-based Signals using Machine Learning
Electroencephalography (EEG) is a widely used technique for measuring brain activity. EEG-based signals can reveal a persons emotional state, as they directly reflect activity in different brain regions. Emotion-aware sy…
Emotion ClassificationEmotion Recognition