A Novel Real-Time Text-to-Speech System Using Raspberry Pi for Assisting the Visually Impaired

Visual impairment is one of the most significant challenges facing humanity, especially in an era where information is frequently conveyed through text rather than voice. To address this, the proposed system is designed to assist individuals with visual impairments. This paper presents the development of a real-time Text-to-Speech (TTS) embedded system based on the Raspberry Pi 4. Our system incorporates a novel approach to enhance the accuracy of text recognition using Optical Character Recognition (OCR) from images. Specifically, a series of preprocessing steps are employed, selected dynamically by a decision-making process based on the content of the image. The image processing is handled using OpenCV2, while the conversion of text to speech is achieved through the pyttsx3 Python library. The entire system is implemented and tested on a Raspberry Pi 4, connected to a USB Full HD camera for high-resolution image acquisition, and controlled via the Traffic HAT-LED module. Experimental results demonstrate that our system achieves a minimum accuracy of 88.33% in text recognition from images.