Real-Time Language Translator Using Raspberry Pi and Python

Abstract

Language diversity across the globe poses significant challenges to seamless human interaction, particularly in domains such as healthcare, academia, commerce, and tourism. Countries with high linguistic diversity, such as India, often require individuals to depend on human interpreters for cross-language communication — a resource that is expensive and inconsistently available. This study proposes a novel embedded system solution: a portable, cost-effective Real-Time Language Translator built on the Raspberry Pi platform and developed using Python. The system acquires spoken input via a microphone, applies automated speech recognition (ASR) to generate text, employs machine translation to convert the text into a chosen target language, and finally synthesizes the translated content as audible speech. The implementation leverages widely-used Python libraries, namely SpeechRecognition, Googletrans, gTTS, and PyAudio. Evaluation results demonstrate translation accuracy ranging

from 85% to 95%, influenced primarily by pronunciation quality and network stability. This prototype effectively showcases the integration of embedded computing with natural language processing technologies.