TEXT TO SPEECH & SPEECH TO TEXT CONVERTER

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Archana Chaudhari Sanket Shinde Yash Sonone Sonone Siddhant Sumare

Abstract

This research introduces a Python-powered Text-To-Speech (TTS) and Speech-To-Text (STT) converter, leveraging the gTTS and SpeechRecognition libraries with Tkinter for the graphical user interface. The TTS component utilizes gTTS to transform text into natural-sounding speech, promoting accessibility for auditory learners. Concurrently, the STT functionality employs SpeechRecognition to capture spoken input via a microphone, converting it into text. The system prioritizes user experience through error handling, user feedback, and a clean GUI. Threading enhances responsiveness, crucial during speech recognition. The project's modularity facilitates maintenance and potential expansions, addressing usability and accessibility concerns. The integration of these technologies contributes to the field of human-computer interaction and assistive technologies. Results showcase the system's efficacy in providing a seamless experience for users requiring efficient text and speech interactions in a Python environment. The open-source nature encourages collaborative development for diverse applications, including education and accessibility solutions.

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Articles

References

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