Speech has long been a barrier to effective communication and connection, persisting as a challenge in our increasingly interconnected world. This research paper introduces a transformative solution to this persistent obstacle an end-to-end speech conversion framework tailored for Hindi-to-English translation, culminating in the synthesis of English audio. By integrating cutting-edge technologies such as XLSR Wav2Vec2 for automatic speech recognition (ASR), mBART for neural machine translation (NMT), and a Text-to-Speech (TTS) synthesis component, this framework offers a unified and seamless approach to cross-lingual communication. We delve into the intricate details of each component, elucidating their individual contributions and exploring the synergies that enable a fluid transition from spoken Hindi to synthesized English audio.
@article{arxiv.2401.06183,
title = {End to end Hindi to English speech conversion using Bark, mBART and a finetuned XLSR Wav2Vec2},
author = {Aniket Tathe and Anand Kamble and Suyash Kumbharkar and Atharva Bhandare and Anirban C. Mitra},
journal= {arXiv preprint arXiv:2401.06183},
year = {2024}
}