Papers Emotion Classification
“Emotion Classification” 태그가 달린 논문 540편 · 필터 해제
AfroXLMR-Social: Adapting Pre-trained Language Models for African Languages Social Media Text
Language models built from various sources are the foundation of today's NLP progress. However, for many low-resource languages, the diversity of domains is often limited -- more biased to a religious domain, which impac…
Continual PretrainingEmotion ClassificationSentiment AnalysisMachine learning based animal emotion classification using audio signals
This paper presents the machine learning approach to the automated classification of a dog's emotional state based on the processing and recognition of audio signals. It offers helpful information for improving human-mac…
Emotion ClassificationSymbolic Audio Classification via Modal Decision Tree Learning
The range of potential applications of acoustic analysis is wide. Classification of sounds, in particular, is a typical machine learning task that received a lot of attention in recent years. The most common approaches t…
Audio ClassificationClassificationEmotion ClassificationSound ClassificationQieemo: Speech Is All You Need in the Emotion Recognition in Conversations
Emotion recognition plays a pivotal role in intelligent human-machine interaction systems. Multimodal approaches benefit from the fusion of diverse modalities, thereby improving the recognition accuracy. However, the lac…
AllAutomatic Speech RecognitionAutomatic Speech Recognition (ASR)Emotion Classification+3A novel Fourier Adjacency Transformer for advanced EEG emotion recognition
EEG emotion recognition faces significant hurdles due to noise interference, signal nonstationarity, and the inherent complexity of brain activity which make accurately emotion classification. In this study, we present t…
EEGEEG Emotion RecognitionEmotion ClassificationEmotion RecognitionContinuous Adversarial Text Representation Learning for Affective Recognition
While pre-trained language models excel at semantic understanding, they often struggle to capture nuanced affective information critical for affective recognition tasks. To address these limitations, we propose a novel f…
Adversarial TextContrastive LearningEmotion ClassificationRepresentation LearningLotus at SemEval-2025 Task 11: RoBERTa with Llama-3 Generated Explanations for Multi-Label Emotion Classification
This paper presents a novel approach for multi-label emotion detection, where Llama-3 is used to generate explanatory content that clarifies ambiguous emotional expressions, thereby enhancing RoBERTa's emotion classifica…
ClassificationEmotion ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONVANPY: Voice Analysis Framework
Voice data is increasingly being used in modern digital communications, yet there is still a lack of comprehensive tools for automated voice analysis and characterization. To this end, we developed the VANPY (Voice Analy…
Action DetectionActivity DetectionClassificationEmotion Classification+2A Novel Dialect-Aware Framework for the Classification of Arabic Dialects and Emotions
Arabic is one of the oldest languages still in use today. As a result, several Arabic-speaking regions have developed dialects that are unique to them. Dialect and emotion recognition have various uses in Arabic text ana…
Emotion ClassificationEmotion RecognitionCross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition
Emotion recognition has a wide range of applications in human-computer interaction, marketing, healthcare, and other fields. In recent years, the development of deep learning technology has provided new methods for emoti…
cross-modal alignmentEmotion ClassificationEmotion RecognitionMarketing+1Characteristic-Specific Partial Fine-Tuning for Efficient Emotion and Speaker Adaptation in Codec Language Text-to-Speech Models
Recently, emotional speech generation and speaker cloning have garnered significant interest in text-to-speech (TTS). With the open-sourcing of codec language TTS models trained on massive datasets with large-scale param…
Emotion ClassificationSpeaker Identificationtext-to-speechText to SpeechLarge Vision-Language Models for Knowledge-Grounded Data Annotation of Memes
Memes have emerged as a powerful form of communication, integrating visual and textual elements to convey humor, satire, and cultural messages. Existing research has focused primarily on aspects such as emotion classific…
Emotion ClassificationImage CaptioningRetrievalText RetrievalRepresentation Learning with Parameterised Quantum Circuits for Advancing Speech Emotion Recognition
Quantum machine learning (QML) offers a promising avenue for advancing representation learning in complex signal domains. In this study, we investigate the use of parameterised quantum circuits (PQCs) for speech emotion …
Emotion ClassificationEmotion RecognitionQuantum Machine LearningRepresentation Learning+1AIMA at SemEval-2024 Task 3: Simple Yet Powerful Emotion Cause Pair Analysis
The SemEval-2024 Task 3 presents two subtasks focusing on emotion-cause pair extraction within conversational contexts. Subtask 1 revolves around the extraction of textual emotion-cause pairs, where causes are defined an…
Emotion-Cause Pair ExtractionEmotion ClassificationSentiment Analysis in Twitter Social Network Centered on Cryptocurrencies Using Machine Learning
Cryptocurrency is a digital currency that uses blockchain technology with secure encryption. Due to the decentralization of these currencies, traditional monetary systems and the capital market of each they, can influenc…
Emotion ClassificationSentiment AnalysisTwitter Sentiment AnalysisDeep Learning-Based Feature Fusion for Emotion Analysis and Suicide Risk Differentiation in Chinese Psychological Support Hotlines
Mental health is a critical global public health issue, and psychological support hotlines play a pivotal role in providing mental health assistance and identifying suicide risks at an early stage. However, the emotional…
Emotion ClassificationEmotion RecognitionEmoNeXt: an Adapted ConvNeXt for Facial Emotion Recognition
Facial expressions play a crucial role in human communication serving as a powerful and impactful means to express a wide range of emotions. With advancements in artificial intelligence and computer vision, deep neural n…
Deep LearningEmotion ClassificationEmotion RecognitionFacial Emotion Recognition+1Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding
Large Language Models (LLMs) show promising learning and reasoning abilities. Compared to other NLP tasks, multilingual and multi-label emotion evaluation tasks are under-explored in LLMs. In this paper, we present Ethio…
DecoderEmotion ClassificationCross-Task Inconsistency Based Active Learning (CTIAL) for Emotion Recognition
Emotion recognition is a critical component of affective computing. Training accurate machine learning models for emotion recognition typically requires a large amount of labeled data. Due to the subtleness and complexit…
Active LearningCross-corpusEmotion ClassificationEmotion RecognitionSentiXRL: An advanced large language Model Framework for Multilingual Fine-Grained Emotion Classification in Complex Text Environment
With strong expressive capabilities in Large Language Models(LLMs), generative models effectively capture sentiment structures and deep semantics, however, challenges remain in fine-grained sentiment classification acros…
ClassificationDecision MakingEmotion ClassificationLanguage Modeling+6