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Towards Computational Linguistics in Minangkabau Language: Studies on Sentiment Analysis and Machine Translation

arXiv 2009.09309 ↗First posted 19 Sep 2020cs.CLcited by 16

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Abstract (arXiv)

Although some linguists (Rusmali et al., 1985; Crouch, 2009) have fairly attempted to define the morphology and syntax of Minangkabau, information processing in this language is still absent due to the scarcity of the annotated resource. In this work, we release two Minangkabau corpora: sentiment analysis and machine translation that are harvested and constructed from Twitter and Wikipedia. We conduct the first computational linguistics in Minangkabau language employing classic machine learning and sequence-to-sequence models such as LSTM and Transformer. Our first experiments show that the classification performance over Minangkabau text significantly drops when tested with the model trained in Indonesian. Whereas, in the machine translation experiment, a simple word-to-word translation using a bilingual dictionary outperforms LSTM and Transformer model in terms of BLEU score.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Sep 2020.

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Citing papers per year: 2022: 4; 2023: 6; 2024: 5; 2025: 1.

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  1. 2023Glot500: Scaling Multilingual Corpora and Language Models to 500 Languagescited by 116
  2. 2022NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languagescited by 67
  3. 2022One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesiacited by 65
  4. 2023Large Language Models Only Pass Primary School Exams in Indonesia: A Comprehensive Test on IndoMMLUcited by 53
  5. 2024SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languagescited by 41
  6. 2022NusaCrowd: Open Source Initiative for Indonesian NLP Resourcescited by 38
  7. 2024Goldfish: Monolingual Language Models for 350 Languagescited by 27
  8. 2024EMMA-500: Enhancing Massively Multilingual Adaptation of Large Language Modelscited by 16
  9. 2023Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Modelscited by 7
  10. 2024Zero-shot Sentiment Analysis in Low-Resource Languages Using a Multilingual Sentiment Lexiconcited by 7
  11. 2023NusaWrites: Constructing High-Quality Corpora for Underrepresented and Extremely Low-Resource Languagescited by 4
  12. 2024Constructing and Expanding Low-Resource and Underrepresented Parallel Datasets for Indonesian Local Languagescited by 3
4 more
  1. 2025SEA-BED: How Do Embedding Models Represent Southeast Asian Languages?cited by 2
  2. 2022Location-based Twitter Filtering for the Creation of Low-Resource Language Datasets in Indonesian Local Languagescited by 1
  3. 2023Sejarah dan Perkembangan Teknik Natural Language Processing (NLP) Bahasa Indonesia: Tinjauan tentang sejarah, perkembangan teknologi, dan aplikasi NLP dalam bahasa Indonesiacited by 0
  4. 2023Replicable Benchmarking of Neural Machine Translation (NMT) on Low-Resource Local Languages in Indonesiacited by 0