Dan John Velasco


2025

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Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia
Samuel Cahyawijaya | Holy Lovenia | Joel Ruben Antony Moniz | Tack Hwa Wong | Mohammad Rifqi Farhansyah | Thant Thiri Maung | Frederikus Hudi | David Anugraha | Muhammad Ravi Shulthan Habibi | Muhammad Reza Qorib | Amit Agarwal | Joseph Marvin Imperial | Hitesh Laxmichand Patel | Vicky Feliren | Bahrul Ilmi Nasution | Manuel Antonio Rufino | Genta Indra Winata | Rian Adam Rajagede | Carlos Rafael Catalan | Mohamed Fazli Mohamed Imam | Priyaranjan Pattnayak | Salsabila Zahirah Pranida | Kevin Pratama | Yeshil Bangera | Adisai Na-Thalang | Patricia Nicole Monderin | Yueqi Song | Christian Simon | Lynnette Hui Xian Ng | Richardy Lobo Sapan | Taki Hasan Rafi | Bin Wang | Supryadi | Kanyakorn Veerakanjana | Piyalitt Ittichaiwong | Matthew Theodore Roque | Karissa Vincentio | Takdanai Kreangphet | Phakphum Artkaew | Kadek Hendrawan Palgunadi | Yanzhi Yu | Rochana Prih Hastuti | William Nixon | Mithil Bangera | Adrian Xuan Wei Lim | Aye Hninn Khine | Hanif Muhammad Zhafran | Teddy Ferdinan | Audra Aurora Izzani | Ayushman Singh | Evan Evan | Jauza Akbar Krito | Michael Anugraha | Fenal Ashokbhai Ilasariya | Haochen Li | John Amadeo Daniswara | Filbert Aurelian Tjiaranata | Eryawan Presma Yulianrifat | Can Udomcharoenchaikit | Fadil Risdian Ansori | Mahardika Krisna Ihsani | Giang Nguyen | Anab Maulana Barik | Dan John Velasco | Rifo Ahmad Genadi | Saptarshi Saha | Chengwei Wei | Isaiah Edri W. Flores | Kenneth Chen Ko Han | Anjela Gail D. Santos | Wan Shen Lim | Kaung Si Phyo | Tim Santos | Meisyarah Dwiastuti | Jiayun Luo | Jan Christian Blaise Cruz | Ming Shan Hee | Ikhlasul Akmal Hanif | M.Alif Al Hakim | Muhammad Rizky Sya’ban | Kun Kerdthaisong | Lester James Validad Miranda | Fajri Koto | Tirana Noor Fatyanosa | Alham Fikri Aji | Jostin Jerico Rosal | Jun Kevin | Robert Wijaya | Onno P. Kampman | Ruochen Zhang | Börje F. Karlsson | Peerat Limkonchotiwat
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Despite Southeast Asia’s (SEA) extraordinary linguistic and cultural diversity, the region remains significantly underrepresented in vision-language (VL) research, resulting in AI models that inadequately capture SEA cultural nuances. To fill this gap, we present SEA-VL, an open-source initiative dedicated to developing culturally relevant high-quality datasets for SEA languages. By involving contributors from SEA countries, SEA-VL ensures better cultural relevance and diversity, fostering greater inclusivity of underrepresented languages and cultural depictions in VL research. Our methodology employed three approaches: community-driven crowdsourcing with SEA contributors, automated image crawling, and synthetic image generation. We evaluated each method’s effectiveness in capturing cultural relevance. We found that image crawling achieves approximately ~85% cultural relevance while being more cost- and time-efficient than crowdsourcing, whereas synthetic image generation failed to accurately reflect SEA cultural nuances and contexts. Collectively, we gathered 1.28 million SEA culturally relevant images, more than 50 times larger than other existing datasets. This work bridges the representation gap in SEA, establishes a foundation for developing culturally aware AI systems for this region, and provides a replicable framework for addressing representation gaps in other underrepresented regions.

2024

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SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages
Holy Lovenia | Rahmad Mahendra | Salsabil Maulana Akbar | Lester James V. Miranda | Jennifer Santoso | Elyanah Aco | Akhdan Fadhilah | Jonibek Mansurov | Joseph Marvin Imperial | Onno P. Kampman | Joel Ruben Antony Moniz | Muhammad Ravi Shulthan Habibi | Frederikus Hudi | Railey Montalan | Ryan Ignatius | Joanito Agili Lopo | William Nixon | Börje F. Karlsson | James Jaya | Ryandito Diandaru | Yuze Gao | Patrick Amadeus | Bin Wang | Jan Christian Blaise Cruz | Chenxi Whitehouse | Ivan Halim Parmonangan | Maria Khelli | Wenyu Zhang | Lucky Susanto | Reynard Adha Ryanda | Sonny Lazuardi Hermawan | Dan John Velasco | Muhammad Dehan Al Kautsar | Willy Fitra Hendria | Yasmin Moslem | Noah Flynn | Muhammad Farid Adilazuarda | Haochen Li | Johanes Lee | R. Damanhuri | Shuo Sun | Muhammad Reza Qorib | Amirbek Djanibekov | Wei Qi Leong | Quyet V. Do | Niklas Muennighoff | Tanrada Pansuwan | Ilham Firdausi Putra | Yan Xu | Tai Ngee Chia | Ayu Purwarianti | Sebastian Ruder | William Tjhi | Peerat Limkonchotiwat | Alham Fikri Aji | Sedrick Keh | Genta Indra Winata | Ruochen Zhang | Fajri Koto | Zheng-Xin Yong | Samuel Cahyawijaya
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Southeast Asia (SEA) is a region rich in linguistic diversity and cultural variety, with over 1,300 indigenous languages and a population of 671 million people. However, prevailing AI models suffer from a significant lack of representation of texts, images, and audio datasets from SEA, compromising the quality of AI models for SEA languages. Evaluating models for SEA languages is challenging due to the scarcity of high-quality datasets, compounded by the dominance of English training data, raising concerns about potential cultural misrepresentation. To address these challenges, through a collaborative movement, we introduce SEACrowd, a comprehensive resource center that fills the resource gap by providing standardized corpora in nearly 1,000 SEA languages across three modalities. Through our SEACrowd benchmarks, we assess the quality of AI models on 36 indigenous languages across 13 tasks, offering valuable insights into the current AI landscape in SEA. Furthermore, we propose strategies to facilitate greater AI advancements, maximizing potential utility and resource equity for the future of AI in Southeast Asia.

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Samsung R&D Institute Philippines @ WMT 2024 Indic MT Task
Matthew Theodore Roque | Carlos Rafael Catalan | Dan John Velasco | Manuel Antonio Rufino | Jan Christian Blaise Cruz
Proceedings of the Ninth Conference on Machine Translation

This paper presents the methodology developed by the Samsung R&D Institute Philippines (SRPH) Language Intelligence Team (LIT) for the WMT 2024 Shared Task on Low-Resource Indic Language Translation. We trained standard sequence-to-sequence Transformer models from scratch for both English-to-Indic and Indic-to-English translation directions. Additionally, we explored data augmentation through backtranslation and the application of noisy channel reranking to improve translation quality. A multilingual model trained across all language pairs was also investigated. Our results demonstrate the effectiveness of the multilingual model, with significant performance improvements observed in most language pairs, highlighting the potential of shared language representations in low-resource translation scenarios.

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Samsung R&D Institute Philippines @ WMT 2024 Low-resource Languages of Spain Shared Task
Dan John Velasco | Manuel Antonio Rufino | Jan Christian Blaise Cruz
Proceedings of the Ninth Conference on Machine Translation

This paper details the submission of Samsung R&D Institute Philippines (SRPH) Language Intelligence Team (LIT) to the WMT 2024 Low-resource Languages of Spain shared task. We trained translation models for Spanish to Aragonese, Spanish to Aranese/Occitan, and Spanish to Asturian using a standard sequence-to-sequence Transformer architecture, augmenting it with a noisy-channel reranking strategy to select better outputs during decoding. For Spanish to Asturian translation, our method reaches comparable BLEU scores to a strong commercial baseline translation system using only constrained data, backtranslations, noisy channel reranking, and a shared vocabulary spanning all four languages.

2023

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Practical Approaches for Low-Resource Named Entity Recognition of Filipino Telecommunications Domain
Kyle Chan | Kaye Ann De Las Alas | Charles Orcena | Dan John Velasco | Qyle John San Juan | Charibeth Cheng
Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation

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Towards Automatic Construction of Filipino WordNet: Word Sense Induction and Synset Induction Using Sentence Embeddings
Dan John Velasco | Axel Alba | Trisha Gail Pelagio | Bryce Anthony Ramirez | Jan Christian Blaise Cruz | Unisse Chua | Briane Paul Samson | Charibeth Cheng
Proceedings of the First Workshop in South East Asian Language Processing

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