Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | 2025 IEEE International Conference on Smart Computing (SMARTCOMP) |
| Pages | 246-248 |
| Number of pages | 3 |
| ISBN (Electronic) | 979-8-3315-8646-1 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 11th IEEE International Conference on Smart Computing, SMARTCOMP 2025 - Cork, Ireland Duration: 16 Jun 2025 → 19 Jun 2025 |
Conference
| Conference | 11th IEEE International Conference on Smart Computing, SMARTCOMP 2025 |
|---|---|
| Country/Territory | Ireland |
| City | Cork |
| Period | 16/06/25 → 19/06/25 |
Keywords
- large language models
- mobile application
- speech therapy
- stammering
- stuttering