WordWhiz: An AI-Powered Assistive Tool for Dyslexia Support

Abstract

Dyslexia is a neurodevelopmental learning disorder that affects reading fluency, spelling accuracy, and written expression, often resulting in academic difficulties and reduced self-confidence. Conventional assistive tools provide limited support by addressing isolated learning challenges. This paper presents WordWhiz, an AI-powered assistive system designed to enhance reading comprehension and writing accuracy for individuals with dyslexia. The proposed system integrates text-to-speech with word highlighting, speech-to- text with grammar correction, phonetic spelling assistance, and transformer-based sentence simplification within a unified framework. The system is implemented as a device-based application to ensure low latency, data privacy, and offline usability. Experimental evaluation demonstrates improved text readability, reduced grammatical errors, and enhanced user engagement, validating the effectiveness of AI-driven assistive technologies in inclusive education.

Introduction

Dyslexia creates persistent challenges in reading, writing, and spelling, which conventional learning tools often fail to address. WordWhiz is an AI-driven assistive system designed to support dyslexic learners by adapting to individual needs through personalized, interactive, and accessible language assistance. The system integrates text-to-speech, speech-to-text, grammar correction, phonetic spelling guidance, and sentence simplification, reducing cognitive load and enhancing literacy skills.

Key Points:

1. Motivation and Research Gap: Existing tools offer isolated functionalities like TTS, STT, grammar correction, or spelling assistance, but lack an integrated, device-based solution. WordWhiz addresses this by combining multiple assistive features in a single, low-latency, privacy-conscious system.

2. System Features:

   • Text-to-Speech (TTS): Converts text to audio, helping users comprehend complex passages.

   • Speech-to-Text (STT): Allows voice input, reducing typing effort and improving accessibility.

   • Grammar Correction: Corrects sentence structure, verb agreement, and punctuation issues.

   • Phonetic Spelling Suggestion: Offers corrections for sound-based spelling errors.

   • Sentence Simplification: Uses transformer models to convert complex sentences into simpler forms while preserving meaning.

3. Architecture and Implementation: Modular, layered design with a frontend UI, backend processing, and NLP model layer. Python-based backend integrates T5 transformer models, grammar correction, phonetic assistance, and speech modules. Device-based processing ensures data privacy, low latency, and offline functionality.

4. Results: Evaluations show that WordWhiz improves readability, writing accuracy, and comprehension. Speech-based features are reliable, and the dyslexia-friendly interface enhances usability. The system effectively combines multiple assistive technologies, providing a holistic support platform compared to traditional single-feature tools.

5. Future Scope: Potential improvements include personalization based on user learning patterns, multilingual support, advanced feedback mechanisms, and large-scale evaluations to assess long-term educational impact.

Conclusion

This paper presented WordWhiz, an AI-powered assistive system developed to support individuals with dyslexia in reading, writing, and text comprehension. The system integrates multiple natural language processing and speech-based functionalities, including sentence simplification, grammar correction, phonetic spelling assistance, text-to-speech, and speech-to-text, into a unified application. By combining these features, WordWhiz addresses the limitations of traditional assistive tools that offer isolated support mechanisms. Experimental results indicate that the proposed system improves text readability and enhances writing accuracy for dyslexic learners. The sentence simplification module effectively reduces linguistic complexity while preserving the original meaning, thereby lowering cognitive load and improving comprehension. Grammar correction and phonetic spelling assistance help minimize common writing errors, while speech-based features provide alternative interaction modes that improve accessibility and learning flexibility. The modular architecture of WordWhiz enables efficient coordination between the user interface, processing layer, and language models, ensuring smooth operation and scalability. Its device-based implementation promotes data privacy, reduces dependency on continuous internet connectivity, and provides low-latency response, making it suitable for practical deployment in educational environments. Overall, WordWhiz demonstrates the potential of AI-driven assistive technologies in supporting inclusive learning for individuals with dyslexia. The results validate the effectiveness of integrating text and speech processing techniques within a single system to improve usability and learning outcomes. The proposed approach provides a foundation for future advancements in personalized and adaptive dyslexia support systems.

References

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Copyright

Copyright © 2026 Niya L R, Edwin Paulose, Pooja Krishna S, Ligin Saji, Mr. Anup Mathew Abraham. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.