Papers Emotion Classification
“Emotion Classification” 태그가 달린 논문 540편 · 필터 해제
Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain Adaptation
Emotion recognition has significant potential in healthcare and affect-sensitive systems such as brain-computer interfaces (BCIs). However, challenges such as the high cost of labeled data and variability in electroencep…
Domain AdaptationEEGElectroencephalogram (EEG)Emotion Classification+2Emotion Classification of Children Expressions
This paper proposes a process for a classification model for the facial expressions. The proposed process would aid in specific categorisation of children's emotions from 2 emotions namely 'Happy' and 'Sad'. Since the ex…
ClassificationData AugmentationEmotion ClassificationEmotion Recognition+1Exploring Vision Language Models for Facial Attribute Recognition: Emotion, Race, Gender, and Age
Technologies for recognizing facial attributes like race, gender, age, and emotion have several applications, such as surveillance, advertising content, sentiment analysis, and the study of demographic trends and social …
AttributeEmotion ClassificationEmotion RecognitionSentiment AnalysisMulti-aspect Depression Severity Assessment via Inductive Dialogue System
With the advancement of chatbots and the growing demand for automatic depression detection, identifying depression in patient conversations has gained more attention. However, prior methods often assess depression in a b…
Depression DetectionEmotion ClassificationResponse GenerationLeaving Some Facial Features Behind
Facial expressions are crucial to human communication, offering insights into emotional states. This study examines how specific facial features influence emotion classification, using facial perturbations on the Fer2013…
ClassificationEmotion ClassificationEmotion RecognitionVEMOCLAP: A video emotion classification web application
We introduce VEMOCLAP: Video EMOtion Classifier using Pretrained features, the first readily available and open-source web application that analyzes the emotional content of any user-provided video. We improve our previo…
ClassificationEmotion ClassificationVideo Emotion RecognitionM2M-Gen: A Multimodal Framework for Automated Background Music Generation in Japanese Manga Using Large Language Models
This paper introduces M2M Gen, a multi modal framework for generating background music tailored to Japanese manga. The key challenges in this task are the lack of an available dataset or a baseline. To address these chal…
Emotion ClassificationMusic GenerationTinyEmo: Scaling down Emotional Reasoning via Metric Projection
This paper introduces TinyEmo, a family of small multi-modal language models for emotional reasoning and classification. Our approach features: (1) a synthetic emotional instruct dataset for both pre-training and fine-tu…
Bias DetectionClassificationEmotion ClassificationLanguage Modeling+2Song Emotion Classification of Lyrics with Out-of-Domain Data under Label Scarcity
Songs have been found to profoundly impact human emotions, with lyrics having significant power to stimulate emotional changes in the audience. There is a scarcity of large, high quality in-domain datasets for lyrics-bas…
ClassificationEmotion ClassificationA Multi-task Learning Framework for Evaluating Machine Translation of Emotion-loaded User-generated Content
Machine translation (MT) of user-generated content (UGC) poses unique challenges, including handling slang, emotion, and literary devices like irony and sarcasm. Evaluating the quality of these translations is challengin…
Emotion ClassificationMachine TranslationMulti-Task LearningSentence+1Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss Function
In multi-label emotion classification, particularly for low-resource languages like Arabic, the challenges of class imbalance and label correlation hinder model performance, especially in accurately predicting minority e…
ClassificationContrastive LearningEmotion ClassificationMeta-Learning+2Recent Advancement of Emotion Cognition in Large Language Models
Emotion cognition in large language models (LLMs) is crucial for enhancing performance across various applications, such as social media, human-computer interaction, and mental health assessment. We explore the current l…
Contrastive LearningEmotion ClassificationResponse GenerationZSDEVC: Zero-Shot Diffusion-based Emotional Voice Conversion with Disentangled Mechanism
The human voice conveys not just words but also emotional states and individuality. Emotional voice conversion (EVC) modifies emotional expressions while preserving linguistic content and speaker identity, improving appl…
Emotion ClassificationVoice ConversionTowards More Accurate Prediction of Human Empathy and Emotion in Text and Multi-turn Conversations by Combining Advanced NLP, Transformers-based Networks, and Linguistic Methodologies
Based on the WASSA 2022 Shared Task on Empathy Detection and Emotion Classification, we predict the level of empathic concern and personal distress displayed in essays. For the first stage of this project we implemented …
Emotion ClassificationSentenceAll rivers run into the sea: Unified Modality Brain-like Emotional Central Mechanism
In the field of affective computing, fully leveraging information from a variety of sensory modalities is essential for the comprehensive understanding and processing of human emotions. Inspired by the process through wh…
AllDynamic Facial Expression RecognitionEmotion ClassificationFacial Expression RecognitionAn Explainable Fast Deep Neural Network for Emotion Recognition
In the context of artificial intelligence, the inherent human attribute of engaging in logical reasoning to facilitate decision-making is mirrored by the concept of explainability, which pertains to the ability of a mode…
AttributeEmotion ClassificationEmotion RecognitionExplainable artificial intelligence+2Enhancing Emotion Prediction in News Headlines: Insights from ChatGPT and Seq2Seq Models for Free-Text Generation
Predicting emotions elicited by news headlines can be challenging as the task is largely influenced by the varying nature of people's interpretations and backgrounds. Previous works have explored classifying discrete emo…
ClassificationEmotion ClassificationExplanation GenerationLanguage Modelling+2Emotion Detection through Body Gesture and Face
The project leverages advanced machine and deep learning techniques to address the challenge of emotion recognition by focusing on non-facial cues, specifically hands, body gestures, and gestures. Traditional emotion rec…
Emotion ClassificationEmotion RecognitionPose EstimationFlood of Techniques and Drought of Theories: Emotion Mining in Disasters
Emotion mining has become a crucial tool for understanding human emotions during disasters, leveraging the extensive data generated on social media platforms. This paper aims to summarize existing research on emotion min…
Emotion ClassificationSentiment AnalysisEmpathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents
We introduce the concept of "empathic grounding" in conversational agents as an extension of Clark's conceptualization of grounding in conversation in which the grounding criterion includes listener empathy for the speak…
Emotional IntelligenceEmotion ClassificationHuman Interaction RecognitionLanguage Modelling+4