scb-mt-en-th-2020: A Large English-Thai Parallel Corpus
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Abstract (arXiv)
The primary objective of our work is to build a large-scale English-Thai dataset for machine translation. We construct an English-Thai machine translation dataset with over 1 million segment pairs, curated from various sources, namely news, Wikipedia articles, SMS messages, task-based dialogs, web-crawled data and government documents. Methodology for gathering data, building parallel texts and removing noisy sentence pairs are presented in a reproducible manner. We train machine translation models based on this dataset. Our models' performance are comparable to that of Google Translation API (as of May 2020) for Thai-English and outperform Google when the Open Parallel Corpus (OPUS) is included in the training data for both Thai-English and English-Thai translation. The dataset, pre-trained models, and source code to reproduce our work are available for public use.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Jul 2020.
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Citing papers per year: 2023: 2; 2024: 3; 2025: 2; 2026: 3.
10 papers.
- 2024Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuningcited by 174
- 2023PyThaiNLP: Thai Natural Language Processing in Pythoncited by 27
- 2025Just Go Parallel: Improving the Multilingual Capabilities of Large Language Modelscited by 8
- 2023PhayaThaiBERT: Enhancing a Pretrained Thai Language Model with Unassimilated Loanwordscited by 2
- 2024Representing the Under-Represented: Cultural and Core Capability Benchmarks for Developing Thai Large Language Modelscited by 2
- 2025SEA-BED: How Do Embedding Models Represent Southeast Asian Languages?cited by 2
- 2024Can General-Purpose Large Language Models Generalize to English-Thai Machine Translation ?cited by 1
- 2026MERIT: Multilingual Expert-Reward Informed Tuning for Chinese-Centric Low-Resource Machine Translationcited by 1
- 2026Reference-Grounded Data Curation for Instruction-Following Thai-English Machine Translationcited by 0
- 2026Cross-Lingual Alignment for Decoder-Only Models using MoE Routerscited by 0
- 2026Cross-Lingual Alignment for Decoder-Only Models using MoE Routers1 Oct 2026
- 2026Reference-Grounded Data Curation for Instruction-Following Thai-English Machine Translation28 Sep 2026
- 2026MERIT: Multilingual Expert-Reward Informed Tuning for Chinese-Centric Low-Resource Machine Translation6 Apr 2026
- 2025SEA-BED: How Do Embedding Models Represent Southeast Asian Languages?17 Aug 2025
- 2025Just Go Parallel: Improving the Multilingual Capabilities of Large Language Models16 Jun 2025
- 2024Can General-Purpose Large Language Models Generalize to English-Thai Machine Translation ?22 Oct 2024
- 2024Representing the Under-Represented: Cultural and Core Capability Benchmarks for Developing Thai Large Language Models7 Oct 2024
- 2024Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning9 Feb 2024
- 2023PyThaiNLP: Thai Natural Language Processing in Python7 Dec 2023
- 2023PhayaThaiBERT: Enhancing a Pretrained Thai Language Model with Unassimilated Loanwords21 Nov 2023