Translation of Multilingual Text into Speech for Visually Impaired Person

Today’s human contact is primarily through voice and text. A person must have a proper vision to view and access the information available in the form of text. In any case, individuals who are blind can gather information by using their hearing ability. The proposed method is a camera-based assistive message reading system that allows blind people and travellers to read the E-messages, printed notes, and other materials in their native languages. It integrates the ideas of optical character recognition (OCR), text to voice synthesizer (TTS), and interpreter in the Raspberry Pi. The proposed model coverts the text from verified records or a caption overlay available on an image into machine-readable text. Text-to-Speech conversion has been enabled by employing the OCR operation to sweep and read any language characters and numbers present in an image and interpret the information in any desired language, and lastly produce a voice output of the decoded text. Voice is the output obtained through the Raspberry Pi’s sound jack, which may be heard by using speakers or headphones. The main goal of this research work is to develop and implement a novel model to transcribe the Text to Speech in many dialects.