TRANSLATIONCORRECT: A Unified Framework for Machine Translation Post-Editing with Predictive Error Assistance
Syed Mekael Wasti, Shou-Yi Hung, Christopher Collins, En-Shiun Annie Lee
Abstract
Machine translation (MT) post-editing and research data collection often rely on inefficient, disconnected workflows. We introduce **TranslationCorrect**, an integrated framework designed to streamline these tasks. **TranslationCorrect** combines MT generation using models like NLLB, automated error prediction using models like XCOMET or LLM APIs (providing detailed reasoning), and an intuitive post-editing interface within a single environment. Built with human-computer interaction (HCI) principles in mind to minimize cognitive load, as confirmed by a user study. For translators, it enables them to correct errors and batch translate efficiently. For researchers, **TranslationCorrect** exports high-quality span-based annotations in the Error Span Annotation (ESA) format, using an error taxonomy inspired by Multidimensional Quality Metrics (MQM). These outputs are compatible with state-of-the-art error detection models and suitable for training MT or post-editing systems. Our user study confirms that **TranslationCorrect** significantly improves translation efficiency and user satisfaction over traditional annotation methods.- Anthology ID:
- 2025.acl-demo.53
- Volume:
- Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
- Month:
- July
- Year:
- 2025
- Address:
- Vienna, Austria
- Editors:
- Pushkar Mishra, Smaranda Muresan, Tao Yu
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 551–562
- Language:
- URL:
- https://preview.aclanthology.org/ingestion-acl-25/2025.acl-demo.53/
- DOI:
- Cite (ACL):
- Syed Mekael Wasti, Shou-Yi Hung, Christopher Collins, and En-Shiun Annie Lee. 2025. TRANSLATIONCORRECT: A Unified Framework for Machine Translation Post-Editing with Predictive Error Assistance. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 551–562, Vienna, Austria. Association for Computational Linguistics.
- Cite (Informal):
- TRANSLATIONCORRECT: A Unified Framework for Machine Translation Post-Editing with Predictive Error Assistance (Wasti et al., ACL 2025)
- PDF:
- https://preview.aclanthology.org/ingestion-acl-25/2025.acl-demo.53.pdf