A Voice-Controlled Dialogue System for NPC Interaction using Large Language Models
Milan Wevelsiep, Nicholas Thomas Walker, Nicolas Wagner, Stefan Ultes
Abstract
This paper explores the integration of voice-controlled dialogue systems in narrative-driven video games, addressing the limitations of existing approaches. We propose a hybrid interface that allows players to freely paraphrase predefined dialogue options, combining player expressiveness with narrative cohesion. The prototype was developed in Unity, and a large language model was used to map the transcribed voice input to existing dialogue options. The approach was evaluated in a user study (n=14) that compared the hybrid interface to traditional point-and-click methods. Results indicate the proposed interface enhances player’s degree of joy and perceived freedom while maintaining narrative consistency. The findings provide insights into the design of scalable and engaging voice-controlled systems for interactive storytelling. Future research should focus on reducing latency and refining language model accuracy to further improve user experience and immersion.- Anthology ID:
- 2025.iwsds-1.4
- Volume:
- Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology
- Month:
- May
- Year:
- 2025
- Address:
- Bilbao, Spain
- Editors:
- Maria Ines Torres, Yuki Matsuda, Zoraida Callejas, Arantza del Pozo, Luis Fernando D'Haro
- Venues:
- IWSDS | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 29–38
- Language:
- URL:
- https://preview.aclanthology.org/landing_page/2025.iwsds-1.4/
- DOI:
- Cite (ACL):
- Milan Wevelsiep, Nicholas Thomas Walker, Nicolas Wagner, and Stefan Ultes. 2025. A Voice-Controlled Dialogue System for NPC Interaction using Large Language Models. In Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology, pages 29–38, Bilbao, Spain. Association for Computational Linguistics.
- Cite (Informal):
- A Voice-Controlled Dialogue System for NPC Interaction using Large Language Models (Wevelsiep et al., IWSDS 2025)
- PDF:
- https://preview.aclanthology.org/landing_page/2025.iwsds-1.4.pdf