@inproceedings{alvarez-vidal-oliver-2026-tamtas,
title = "{T}a{MTAS}: Terminology-Aware Machine Translation for Accessible Science. Large Corpus compilation, terminology extraction and data augmentation",
author = "{\'A}lvarez-Vidal, Sergi and
Oliver, Antoni",
editor = "Shterionov, Dimitar and
Vanmassenhove, Eva and
De Sisto, Mirella and
Blain, Fred and
Pourmostafa Roshan Sharami, Javad and
Lepp, Lisa and
Manna, Chiara and
Rescigno, Argentina Anna and
Karakanta, Alina and
Rigouts Terryn, Ayla and
Lardelli, Manuel and
Resende, Natalia and
Murgolo, Elena and
Hackenbuchner, Jani{\c{c}}a and
Zaretskaya, Anna and
Espl{\`a}-Gomis, Miquel and
Etchegoyhen, Thierry and
Gromann, Dagmar and
Bawden, Rachel and
Haddow, Barry and
Szoc, Sara and
Forcada, Mikel and
Moniz, Helena",
booktitle = "Proceedings of the 26th Annual Conference of the {E}uropean Association for Machine Translation (Volume 2)",
month = jun,
year = "2026",
address = "Tilburg, The Netherlands",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2026.eamt-2.16/",
pages = "33--34",
ISBN = "9789403901404",
abstract = "This paper presents the TaMTAS project (Terminology-Aware Machine Translation for Accessible Science), a research project coordinated by the Universitat Oberta de Catalunya (UOC) to develop an open- source translation ecosystem for the Life Sciences. While we provide a general overview of the project{'}s organization into seven Work Packages (WPs) and its col- laborative consortium, this article focuses specifically on the work of WP2. Led by the UOC, this package is responsible for the parallel corpus compilation for five lan- guages (English, Spanish, Catalan, Esto- nian, and Irish), the enhancement of TBX- Tools for terminology extraction, and the development of synthetic data augmenta- tion strategies. These linguistic assets are essential to power the downstream Large Reasoning Models (LRMs) and Automatic Post-Editing (APE) modules, ensuring ter- minological consistency in highly special- ized scientific domains."
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<abstract>This paper presents the TaMTAS project (Terminology-Aware Machine Translation for Accessible Science), a research project coordinated by the Universitat Oberta de Catalunya (UOC) to develop an open- source translation ecosystem for the Life Sciences. While we provide a general overview of the project’s organization into seven Work Packages (WPs) and its col- laborative consortium, this article focuses specifically on the work of WP2. Led by the UOC, this package is responsible for the parallel corpus compilation for five lan- guages (English, Spanish, Catalan, Esto- nian, and Irish), the enhancement of TBX- Tools for terminology extraction, and the development of synthetic data augmenta- tion strategies. These linguistic assets are essential to power the downstream Large Reasoning Models (LRMs) and Automatic Post-Editing (APE) modules, ensuring ter- minological consistency in highly special- ized scientific domains.</abstract>
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%0 Conference Proceedings
%T TaMTAS: Terminology-Aware Machine Translation for Accessible Science. Large Corpus compilation, terminology extraction and data augmentation
%A Álvarez-Vidal, Sergi
%A Oliver, Antoni
%Y Shterionov, Dimitar
%Y Vanmassenhove, Eva
%Y De Sisto, Mirella
%Y Blain, Fred
%Y Pourmostafa Roshan Sharami, Javad
%Y Lepp, Lisa
%Y Manna, Chiara
%Y Rescigno, Argentina Anna
%Y Karakanta, Alina
%Y Rigouts Terryn, Ayla
%Y Lardelli, Manuel
%Y Resende, Natalia
%Y Murgolo, Elena
%Y Hackenbuchner, Janiça
%Y Zaretskaya, Anna
%Y Esplà-Gomis, Miquel
%Y Etchegoyhen, Thierry
%Y Gromann, Dagmar
%Y Bawden, Rachel
%Y Haddow, Barry
%Y Szoc, Sara
%Y Forcada, Mikel
%Y Moniz, Helena
%S Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 2)
%D 2026
%8 June
%I European Association for Machine Translation
%C Tilburg, The Netherlands
%@ 9789403901404
%F alvarez-vidal-oliver-2026-tamtas
%X This paper presents the TaMTAS project (Terminology-Aware Machine Translation for Accessible Science), a research project coordinated by the Universitat Oberta de Catalunya (UOC) to develop an open- source translation ecosystem for the Life Sciences. While we provide a general overview of the project’s organization into seven Work Packages (WPs) and its col- laborative consortium, this article focuses specifically on the work of WP2. Led by the UOC, this package is responsible for the parallel corpus compilation for five lan- guages (English, Spanish, Catalan, Esto- nian, and Irish), the enhancement of TBX- Tools for terminology extraction, and the development of synthetic data augmenta- tion strategies. These linguistic assets are essential to power the downstream Large Reasoning Models (LRMs) and Automatic Post-Editing (APE) modules, ensuring ter- minological consistency in highly special- ized scientific domains.
%U https://aclanthology.org/2026.eamt-2.16/
%P 33-34
Markdown (Informal)
[TaMTAS: Terminology-Aware Machine Translation for Accessible Science. Large Corpus compilation, terminology extraction and data augmentation](https://aclanthology.org/2026.eamt-2.16/) (Álvarez-Vidal & Oliver, EAMT 2026)
ACL