AdCOFE: Advanced Contextual Feature Extraction in Conversations for emotion classification
Emotion recognition in conversations is an important step in various virtual chat bots which require opinion-based feedback, like in social media threads, online support and many more applications. Current Emotion recognition in conversations models face issues like (a) loss of contextual information in between two dialogues of a conversation, (b) failure to give appropriate importance to significant tokens in each utterance and (c) inability to pass on the emotional information from previous utterances.The proposed model of Advanced Contextual Feature Extraction (AdCOFE) addresses these issues by performing unique feature extraction using knowledge graphs, sentiment lexicons and phrases of natural language at all levels (word and position embedding) of the utterances. Experiments on the Emotion recognition in conversations dataset show that AdCOFE is beneficial in capturing emotions in conversations.
Code (0)
등록된 구현이 없습니다.
Tasks
ClassificationEmotion ClassificationEmotion RecognitionGeneral ClassificationKnowledge GraphsPositionSimilar Papers 제목 키워드 기반
Neural Feature Extraction for Contextual Emotion Detection
This paper describes a new approach for the task of contextual emotion detection. The approach is based on a neural feature extractor, composed of a recurrent neural network with an attention mechanism, followed by a cla…
Emotion Recognition in ConversationPOSWord Embeddingspytopicgram: A library for data extraction and topic modeling from Telegram channels
Telegram is a popular platform for public communication, generating large amounts of messages through its channels. pytopicgram is a Python library that helps researchers collect, organize, and analyze these Telegram mes…
RetrievalEnhancing Clinical Concept Extraction with Contextual Embeddings
Neural network-based representations ("embeddings") have dramatically advanced natural language processing (NLP) tasks, including clinical NLP tasks such as concept extraction. Recently, however, more advanced embedding …
Clinical Concept ExtractionLanguage ModellingLarge Language ModelWord EmbeddingsMultimodal Emotion-Cause Pair Extraction in Conversations
Emotion cause analysis has received considerable attention in recent years. Previous studies primarily focused on emotion cause extraction from texts in news articles or microblogs. It is also interesting to discover emo…
ArticlesEmotion Cause ExtractionEmotion-Cause Pair ExtractionEmotion Recognition+1Recognizing Emotion Cause in Conversations
We address the problem of recognizing emotion cause in conversations, define two novel sub-tasks of this problem, and provide a corresponding dialogue-level dataset, along with strong Transformer-based baselines. The dat…
Causal Emotion EntailmentEmotion Cause ExtractionRecognizing Emotion Cause in Conversations