DEMO: EaseTalk: An LLM-Driven Speech Practice Tool for Real-Life Scenarios

Research output: Chapter in Book/Report/Conference proceedingsConference proceedingpeer-review

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 languageEnglish
Title of host publication2025 IEEE International Conference on Smart Computing (SMARTCOMP)
Pages246-248
Number of pages3
ISBN (Electronic)979-8-3315-8646-1
DOIs
Publication statusPublished - 2025
Event11th IEEE International Conference on Smart Computing, SMARTCOMP 2025 - Cork, Ireland
Duration: 16 Jun 202519 Jun 2025

Conference

Conference11th IEEE International Conference on Smart Computing, SMARTCOMP 2025
Country/TerritoryIreland
CityCork
Period16/06/2519/06/25

Keywords

  • large language models
  • mobile application
  • speech therapy
  • stammering
  • stuttering

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