Author Login IJIRT Partner Network (IPN) Login

End-to-End Gujarati Task-Oriented Dialogue Management using Reinforcement Learning

  • Unique Paper ID: 163264
  • Volume: 10
  • Issue: 11
  • PageNo: 2904-2911
  • Abstract:
  • Nowadays, there's an increased demand for dialogue systems in local languages due to the ongoing need for continuous support in specific service domains. Ra-ther than relying solely on human resources, dialogue systems offer a viable solu-tion. Dialogue management plays a pivotal role in determining the most effective actions for the system at each stage. In this study, we introduce a task-oriented dialogue system for Gujarati language, leveraging reinforcement learning. This system comprises three key components: natural language understanding (NLU), Dialogue Management (DM), and Natural Language Generation (NLG). Our model seamlessly interacts with databases, extracting valuable information. Rein-forcement learning is employed specifically for the DM, employing an enhanced Deep Q-learning Network (DQN) strategy to bolster the agent's resilience against environmental noise. Additionally, we propose a unified model for the NLU module, demonstrating its effectiveness through experiments conducted on Guja-rati dialogue datasets. The results showcase the superior performance of our model over the conventional rule-based multi-turn dialogue system for Gujarati dialogues.
Download article email to a friend

Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 11
  • PageNo: 2904-2911

End-to-End Gujarati Task-Oriented Dialogue Management using Reinforcement Learning

Related Articles

Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now

Latest Publication

Archive

View More

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry