Bangla AI: A Framework for Machine Translation Utilizing Large Language Models for Ethnic Media

TL;DR

This paper explores integrating large language models with multi-lingual machine translation to enhance news translation, searching, and categorization in Bangla ethnic media, highlighting potential benefits and ethical considerations.

Contribution

It proposes a theoretical framework for combining LLM and MMT in ethnic media news processes, addressing technical and ethical aspects.

Findings

Framework for LLM and MMT integration in ethnic media

Potential improvements in translation accuracy and efficiency

Discussion of ethical challenges in LLM deployment

Abstract

Ethnic media, which caters to diaspora communities in host nations, serves as a vital platform for these communities to both produce content and access information. Rather than utilizing the language of the host nation, ethnic media delivers news in the language of the immigrant community. For instance, in the USA, Bangla ethnic media presents news in Bangla rather than English. This research delves into the prospective integration of large language models (LLM) and multi-lingual machine translations (MMT) within the ethnic media industry. It centers on the transformative potential of using LLM in MMT in various facets of news translation, searching, and categorization. The paper outlines a theoretical framework elucidating the integration of LLM and MMT into the news searching and translation processes for ethnic media. Additionally, it briefly addresses the potential ethical challenges associated with the incorporation of LLM and MMT in news translation procedures.