Papers Emotion Recognition
“Emotion Recognition” 태그가 달린 논문 2,254편 · 필터 해제
AURAL: Adaptive Latent Reasoning with Joint Chunk for Speech Language Models
Model intelligence and fast response jointly shape the quality of interaction with speech language models, yet remain difficult to achieve together. Explicit chain-of-thought (CoT) improves reasoning and audio understand…
Emotion RecognitionSEA-SpeechBench: A Large-Scale Multitask Benchmark for Speech Understanding Across Southeast Asia
The rapid advancement of audio and multimodal large language models has unlocked transformative speech understanding capabilities, yet evaluation frameworks remain predominantly English-centric, leaving Southeast Asian (…
Emotion RecognitionSpeaker RecognitionSpeech RecognitionQuestion AnsweringCross-lingual Functional Vectors for Emotion Detection in Large Language Models
Function vectors (FVs) have recently emerged as a promising mechanism for steering the behavior of large language models (LLMs) by injecting task-specific latent direction representations derived from in-context demonstr…
Emotion RecognitionDissonance Spectrum explicitly models perceptual frequency interactions for better music understanding
Conventional music representations describe acoustic energy over time and frequency but do not explicitly expose relations among simultaneous frequency components. We introduce the \emph{Dissonance Spectrum} (DS), a nonn…
Music Question AnsweringEmotion RecognitionMulti-Feature Riemannian Hypergraph for Online Test-Time Adaptation of Motor Imagery Brain-Computer Interface
In clinical motor imagery brain-computer interface (MI-BCI) decoding, cross-day transferability and online operation remain two critical challenges. Hypergraphs can improve transferability by capturing higher-order sampl…
Test-time AdaptationEmotion RecognitionTransfer LearningProFocus: Interpreting Affective Experience in Artistic Images with Progressive Visual Focusing
Interpreting the emotional responses triggered by images is central to achieving emotional intelligence. Compared with natural images, visual art is intentionally created to elicit emotional responses from its viewers th…
Representation LearningEmotional IntelligenceEmotion RecognitionEEG-PRIME: Prototype-Aligned Representation Learning with Multi-Level Conditioning for EEG Decoding
Electroencephalography (EEG) decoding models often generalize poorly across datasets and subjects due to domain shifts in acquisition protocols and individual neurophysiology. We propose EEG-PRIME, a two-stage EEG founda…
Representation LearningEmotion RecognitionEeg DecodingBioKD: Selective Physiology-to-Video Knowledge Distillation via Reliability Gate for Emotion Recognition
To address the limitations of video-based emotion recognition under ambiguous or socially masked behavioral cues, as well as the poor deployability of physiological signals, this paper proposes a reliability-aware physio…
Knowledge DistillationEmotion RecognitionEfficient and Interpretable Body-Based Emotion Recognition with Lightweight Temporal Convolutional Networks
Body-based emotion recognition is important for real-time affective systems, but graph-based skeleton models can be computationally expensive. This paper studies whether lightweight temporal convolutional networks (TCNs)…
Emotion ClassificationEmotion RecognitionDifferentiable Logic Gate Networks for Low-Latency EEG Classification on Edge Devices
Real-time EEG classification on edge devices is bottlenecked by the floating-point arithmetic of conventional neural networks. We investigated Differentiable Logic Gate Networks (Diff-Logic) as a hardware-native alternat…
Emotion RecognitionSHAP-Weighted Cross-Modal Expert Fusion for Emotion and Sentiment Recognition: Evidence and Limits
Multimodal emotion and sentiment recognition is commonly addressed by early fusion, which concatenates modalities before classification, or late fusion, which combines independently trained unimodal predictors. Early fus…
Emotion RecognitionGraph-Regularized Deep Learning for EEG-Based Emotion Recognition with Psychologically-Grounded Label Structure
EEG-based emotion recognition is critical for mental health monitoring and affective brain-computer interfaces, yet existing deep learning approaches often treat emotion classes as isolated labels, ignoring their psychol…
Graph Neural NetworkEmotion RecognitionMasked Generative-Contrastive Representation Learning for Cross-Dataset EEG-Based Emotion Recognition
Self-supervised learning (SSL) shows strong potential for cross-dataset transfer by improving feature representation and generalization. However, its application to EEG-based emotion recognition remains largely unexplore…
Self-Supervised LearningRepresentation LearningContrastive LearningEmotion RecognitionEmoteGPT: 3D Human Facial Expressions from Natural Language Descriptions
Precise control of 3D facial expressions from text is crucial for virtual avatars, animation, and human-computer interaction, yet existing text-to-3D methods jointly generate identity, expression, and texture, making fin…
Emotion RecognitionQuantifying the Affective Gap: A Zero-Shot Evaluation of LLMs on Fine-Grained Emotion Taxonomies
Emotion recognition in natural language is a foundational challenge in affective computing, with critical implications for human-computer interaction, mental health support, and conversational AI. This paper presents a r…
Emotion ClassificationEmotion RecognitionRethinking the Role of Feature Engineering and Learning Strategies in Few-Shot Hidden Emotion Recognition
In this paper, we present the solution developed by our team, XInsight Lab, which achieved first place in Track 3 of the 4th EI-MIGA-IJCAI Challenge with a test accuracy of 0.76923. To address the challenge of weak and s…
Multiple Instance LearningEmotion RecognitionFeature EngineeringTemporal Feature Extractors in EEG Foundation Models: A Controlled Comparison Including a Pretrained Time-Series Model
Electroencephalography (EEG) foundation models aim to learn generalizable representations from large-scale brain recordings. However, the role of temporal feature extractors and whether pretrained time-series foundation …
Emotion RecognitionA Hybrid Framework for Song Lyric Annotation Based on Human-LLM Alignment
Emotion recognition of song lyrics is a challenging task since lyrics may not necessarily align with the overall emotion of a song. As a result, lyrics annotation remains largely underexplored. Drawing inspiration from r…
Emotion RecognitionGenerative Learning as a Tool to Improve Perception of Emotional Body Motion Expressions
Emotional body motion expressions are an essential element of non-verbal communication. Effectively conveying these expressions through technology is of utmost importance, for example, with virtual reality avatars and in…
Emotion RecognitionA Comparative Study on Affective Cues in Text Embeddings Across Psychological Emotion Theories
Text encoders are known for their utility in natural language processing, as they are able to efficiently compress inputs into dense vectors while preserving semantics. These models have been applied to affective computi…
Emotion RecognitionSentiment Analysis