Live Multimodal Language Translation System: Integrating Real-Time Text, Voice, Image, and Document Translation

Abstract

The purpose of this study is to develop a Live Multimodal Language Translation System (LMLTS) that facilitates real-time translation of text, voice, image, and document inputs, providing outputs in both text and voice formats. Utilizing advanced technologies such as Google Translate API, speech recognition, text-to-speech (TTS), and Optical Character Recognition (OCR), the system aims to break down language barriers and enhance global communication. Methodologically, the system integrates text preprocessing, speech recognition, and OCR for extracting and translating content across various input forms. The implications of this study suggest that LMLTS can serve as a cost-effective alternative to human translators, promoting effective communication and collaboration in a multilingual world.