Virtual Booth

The TinyTalker project aims to develop an innovative mobile application designed to enhance early language development in children, specifically focusing on English pronunciation. Targeting children in their formative years, the application integrates speech recognition technology, real-time feedback, and gamification to create an engaging and interactive learning environment. By providing children with immediate feedback on their pronunciation, TinyTalker helps improve their speaking abilities. build confidence, and facilitate their educational success. The app's core features include personalized learning paths, speech error detection, and a user-friendly interface tailored for young learners. TinyTalker is aligned with Sustainable Development Goal 4 (Quality Education), aiming to provide accessible, high-quality educational tools to all children, regardless of their background or language proficiency. Furthermore, the app supports SDG 10 (Reduced Inequalities) by offering customized learning experiences to accommodate children with diverse linguistic abilities, including non-native speakers and those with speech delays. The project utilizes an Agile development methodology to ensure iterative and user-centered design, with continuous feedback from users shaping its evolution. As the project moves forward, future work will incorporate data science techniques to further personalize the learning experience, adapting content to each child's progress and needs. This paper presents the detailed system description, design prototype, and the initial stages of TinyTalker, highlighting its potential to contribute to early childhood education and promote equitable learning opportunities.