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Monster Words is an innovative web application designed to support young learners in mastering the spelling of multisyllabic words through an engaging and interactive platform. By integrating text-to-speech technology, the application provides auditory reinforcement, enabling children to hear words pronounced clearly, which enhances their spelling practice and phonetic understanding.
Monster Words is a Python/Flask app using Google Cloud Text-to-Speech (with budget-limited quality) to generate audio for multisyllabic words. It's responsive, child-friendly front-end (HTML/CSS) ensures accessibility across devices. Deployed on Render for scalability, it serves educators, parents, and students efficiently.
The file organisation of the "Monster Words" project is structured with clarity and efficiency, facilitating ease of navigation and maintenance. The repository is divided into key directories: app/ houses Python scripts including __init__.py, main.py, and multisyllabic.py for the Flask application logic; static/ contains images/ and style.css for interface assets; and templates/ stores audio files exam.mp3 and test.mp3 for text-to-speech output. Supporting files README.md and requirements.txt reside at the root level, providing documentation and dependency details. Unnecessary files such as __pycache__ and .DS_Store are excluded, ensuring a concise and focused structure.
The code for "Monster Words" is developed with a focus on readability and maintainability, featuring clear and concise comments to guide other developers. Each significant function or block is annotated to explain its purpose, with emphasis on the "why" behind critical decisions, such as optimisation choices or API integration logic.