Challenge
As conversational AI becomes essential in customer support and other interactive sectors, accurate emotion recognition is crucial. Traditional systems struggle with contextual understanding, limiting accuracy and trust.
Our Approach
The project, titled DialogueTraX: Explainable AI for Emotion Recognition in Conversations, will deliver: (i) context-aware analysis by using advanced transformers to incorporate past and future dialogue turns for better emotional insight, and (ii) interactivity explainability by explaining AI decisions using a transparent module to aid knowledge extraction and debugging.
Expected Outcomes
- Improved Accuracy: Enhanced emotion detection through deeper contextual awareness.
- Increased Trust: Clear, interpretable AI decisions.
- Broad Adaptability: Seamless integration into various AI-driven applications.
The project will additionally deliver an interactive user interface, where individuals can freely interact and gather insights about the predictions. By doing so, our pipeline ensures a trustworthy AI paradigm.
Project Status
Ongoing
Lead Researchers
Aydin Javadov
