DEMO: EaseTalk: An LLM-Driven Speech Practice Tool for Real-Life Scenarios
Stuttering can make everyday conversations challenging, especially in situations that involve unfamiliar people or social pressure. While traditional therapy provides structured support, many individuals struggle to apply those techniques in real-world scenarios. Digital speech tools exist, but most focus on repetitive drills and rarely provide realistic, contextdriven speaking practice. We present EaseTalk, an AI-driven mobile application that allows users to practice real-life conversational scenarios in a supportive, self-paced environment. The app uses speech recognition and prompt-engineered large language models (LLMs) to detect speech disfluencies such as repetitions, prolongations and blocks. EaseTalk aims to empower users through independent, scenario-based speech practice with potential applications extending beyond stuttering into areas like social anxiety, interview preparation and language learning.
Authors
- Fiona Ryan
- Nicole Müller (ORCID: https://orcid.org/0000-0002-4405-5340)
- Malik Muhammad Qirtas
- Andrea Visentin (ORCID: https://orcid.org/0000-0003-3702-4826)
- Pauline Frizelle (ORCID: https://orcid.org/0000-0002-9715-3788)
- Marco Faggiani
Institutions
- University College Cork (IE)
Publication Details
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1109/smartcomp65954.2025.00045
- Primary Topic
- Speech and dialogue systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00