Bridging the digital divide: Where do we stand?

Abstract

As we enter the decade of indigenous languages, it is important to track how much progress is being made in bridging the digital divide. To this end XRI Global and students from the University of Arizona have joined efforts to take inventory of the current data and models that exist for the world’s low-resource languages. By cataloging all the data and models on huggingface, GitHub, Common Voice, and other well-known hubs for training data and AI models, our team has produced a map which shows the current level of support for a large number of low-resource languages

GitHub repository is available here under the text folder
Poster abstract is available here under the title Bridging the digital divide: Where do we stand?

Introduction

Mission statement: All training data and language technology for low-resource languages for a world without language barriers.

The data collection process, filtering, and other stuff were chosed based on the methodologies described in detail in NLLB.

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---
layout: page
title: project
description: a project with a background image
img: /assets/img/12.jpg
---

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Bridging the digital divide: Where do we stand?

Abstract

Introduction

References

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