The use of machine learning and Natural Language Processing (NLP) technologies can assist in the preservation and revitalization of indigenous languages, particularly those classified as "low-resource." Given the increasing digitization of information, the development of translation tools for these languages is of significant importance. These tools not only facilitate better access to digital resources for indigenous communities but also stimulate language preservation efforts and potentially foster more inclusive, equitable societies, as demonstrated by the AmericasNLP workshop since 2021. The focus of this paper is Colombia, a country home to 65 distinct indigenous languages, presenting a vast spectrum of linguistic characteristics. This cultural and linguistic diversity is an inherent pillar of the nation's identity, and safeguarding it has been increasingly challenging given the dwindling number of native speakers and the communities' inclination towards oral traditions. Considering this context, scattered initiatives exist to develop translation systems for these languages. However, these endeavors suffer from a lack of consolidated, comparable data. This paper consolidates a dataset of parallel data in four Colombian indigenous languages - Wayuunaiki, Arhuaco, Inga, and Nasa - gathered from existing digital resources. It also presents the creation of baseline models for future translation and comparison, ultimately serving as a catalyst for incorporating more digital resources progressively.

Translation systems for low-resource Colombian Indigenous languages, a first step towards cultural preservation

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**About this workshop:** AmericasNLP aims to...
* ...encourage research on NLP, computational linguistics, corpus linguistics, and speech around the globe to work on native American languages.
* ...connect researchers and professionals from underrepresented communities and native speakers of endangered languages with the machine learning and natural language processing communities.
* ...promote research on both neural and non-neural machine learning approaches suitable for low-resource languages. [**Read more**](https://turing.iimas.unam.mx/americasnlp/)

W9: The Fourth Workshop on NLP for Indigenous Languages of the Americas (AmericasNLP)

workshop paper

## Welcome to 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics!
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The University of Texas at Austin 
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NAACL 2024

2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics

Sara Palacios

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Translation systems for low-resource Colombian Indigenous languages, a first step towards cultural preservation

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