iikim_translator

This repository contains translation models specifically designed for the Mayan languages, Yucatec Mayan and Chol. It's part of a project aimed at advancing neural machine translation (NMT) for indigenous languages, leveraging Spanish-trained large language models (LLMs) due to the scarcity of comprehensive parallel corpora for these languages.

Overview

Advancing NMT for Indigenous Languages: This project focuses on a case study involving Yucatec Mayan and Chol, two Mayan languages with significant historical and cultural importance yet limited digital resources. By implementing a prompt-based approach to train both one-to-many and many-to-many models, this study demonstrates the viability of using LLMs to improve accessibility and preservation for languages with limited digital resources. The best-performing models reached a ChrF++ score of 50 on the test set, indicating a strong potential for these approaches in real-world applications.

Project Goals

• Develop and refine NMT systems for Mayan languages.
• Bridge the digital gap for Mayan language communities, enhancing access to vital services.
• Promote collaboration and further research in NLP for indigenous languages.

Training

M2M model

./train/m2m100_418M/mayan.sh

T5-base-spanish model

./train/t5-base-spanish/mayan.sh

Testing

M2M model

./test/m2m100_418M/mayan.sh

T5-base-spanish model

./test/t5-base-spanish/mayan.sh

HF Models

Visit the following Hugging Face model repositories to access the pre-trained models:

• M2M100
• T5-base-spanish