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AdCOFE: Advanced Contextual Feature Extraction in conversations for emotion classification.

Vaibhav Bhat1, Anita Yadav1, Sonal Yadav1

  • 1Department of Computer Science, Lakehead University, Thunderbay, Ontario, Canada.

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|January 3, 2022
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Summary

This study introduces Advanced Contextual Feature Extraction (AdCOFE) for better emotion recognition in conversations. The new model effectively captures conversational emotions by addressing context loss and improving information flow between utterances.

Keywords:
ChatbotsDyadic conversationEmotion recognition

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Area of Science:

  • Natural Language Processing
  • Artificial Intelligence
  • Computational Linguistics

Background:

  • Emotion recognition in conversations is crucial for applications like chatbots and social media analysis.
  • Existing models struggle with contextual information loss, token importance, and inter-utterance emotional flow.

Purpose of the Study:

  • To propose an Advanced Contextual Feature Extraction (AdCOFE) model to overcome limitations in conversational emotion recognition.
  • To enhance the accuracy and robustness of emotion detection in dialogues.

Main Methods:

  • AdCOFE utilizes knowledge graphs, sentiment lexicons, and natural language phrases for feature extraction.
  • The model incorporates word and position embeddings to capture nuanced emotional cues.
  • It addresses the loss of contextual information and improves the propagation of emotional states across utterances.

Main Results:

  • Experiments demonstrate AdCOFE's effectiveness in capturing emotions within conversational contexts.
  • The model shows significant improvements over existing methods in emotion recognition tasks.
  • AdCOFE successfully mitigates issues related to contextual information loss and inter-utterance emotional dependency.

Conclusions:

  • AdCOFE provides a robust framework for advanced emotion recognition in conversations.
  • The proposed method enhances the performance of virtual agents requiring opinion-based feedback.
  • This research contributes to more sophisticated and context-aware conversational AI systems.