NusaAksara: A Multimodal and Multilingual Benchmark for Preserving Indonesian Indigenous Scripts
Muhammad Farid Adilazuarda, Musa Izzanardi Wijanarko, Lucky Susanto, Khumaisa Nur’aini, Derry Tanti Wijaya, Alham Fikri Aji
Abstract
Indonesia is rich in languages and scripts. However, most NLP progress has been made using romanized text. In this paper, we present NusaAksara, a novel public benchmark for Indonesian languages that includes their original scripts. Our benchmark covers both text and image modalities and encompasses diverse tasks such as image segmentation, OCR, transliteration, translation, and language identification. Our data is constructed by human experts through rigorous steps. NusaAksara covers 8 scripts across 7 languages, including low-resource languages not commonly seen in NLP benchmarks. Although unsupported by Unicode, the Lampung script is included in this dataset. We benchmark our data across several models, from LLMs and VLMs such as GPT-4o, Llama 3.2, and Aya 23 to task-specific systems such as PP-OCR and LangID, and show that most NLP technologies cannot handle Indonesia’s local scripts, with many achieving near-zero performance.
BibTeX
@inproceedings{adilazuarda-etal-2025-nusaaksara,
title = "{N}usa{A}ksara: A Multimodal and Multilingual Benchmark for Preserving {I}ndonesian Indigenous Scripts",
author = "Adilazuarda, Muhammad Farid and
Wijanarko, Musa Izzanardi and
Susanto, Lucky and
Nur{'}aini, Khumaisa and
Wijaya, Derry Tanti and
Aji, Alham Fikri",
editor = "Che, Wanxiang and
Nabende, Joyce and
Shutova, Ekaterina and
Pilehvar, Mohammad Taher",
booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.acl-long.1377/",
doi = "10.18653/v1/2025.acl-long.1377",
pages = "28371--28401",
ISBN = "979-8-89176-251-0"
}