One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia

Authors

Alham Fikri Aji, Amazon, United States
Genta Indra Winata, Bloomberg
Fajri Koto, The University of Melbourne, Australia
Samuel Cahyawijaya, HKUST, Hong Kong
Ade Romadhony, Telkom University, Indonesia & INACL, Indonesia
Rahmad Mahendra, Universitas Indonesia, Indonesia & INACL, Indonesia
Kemal Kurniawan, The University of Melbourne, Australia & INACL Indonesia
David Moeljadi, Kanda University of International Studies, Japan
Radityo Eko Prasojo, Kata.ai, Indonesia
Timothy Baldwin, The University of Melbourne, Australia & Mohamed Bin Zayed University of Artificial IntelligenceFollow
Jey Han Lau, The University of Melbourne, Australia
Sebastian Ruder, Google Research, United States

Document Type

Article

Publication Title

arXiv

Abstract

NLP research is impeded by a lack of resources and awareness of the challenges presented by underrepresented languages and dialects. Focusing on the languages spoken in Indonesia, the second most linguistically diverse and the fourth most populous nation of the world, we provide an overview of the current state of NLP research for Indonesia’s 700+ languages. We highlight challenges in Indonesian NLP and how these affect the performance of current NLP systems. Finally, we provide general recommendations to help develop NLP technology not only for languages of Indonesia but also other underrepresented languages. Copyright © 2022, The Authors. All rights reserved.

DOI

doi.org/10.48550/arXiv.2203.13357

Publication Date

3-24-2022

Keywords

NLP systems, Computation and Language (cs.CL)

Comments

Preprint: arXiv

Archived with thanks to arXiv

Recommended Citation

A.F. Aji et al, "One country, 700+ languages: NLP challenges for underrepresented languages and dialects in Indonesia", 2022, arXiv:2203.13357v1