@inproceedings{liyanapathirana-etal-2026-copeco,
title = "{COPECO}-Speech: Multimodal Post-Editing with Speech and {LLM}s for Translation Teaching",
author = "Liyanapathirana, Jeevanthi and
Bouillon, Pierrette and
Mutal, Jonathan and
Girletti, Sabrina and
Volkart, Lise",
editor = {Kr{\"u}ger, Ralph and
Kenny, Dorothy and
Castilho, Sheila and
{\'A}lvarez-Vidal, Sergi and
Aranberri, Nora and
Ginel, Mar{\'i}a Isabel Rivas and
Hackenbuchner, Jani{\c{c}}a},
booktitle = "Proceedings of the 1st International Workshop on Teaching {AI}-Based Translation and Technologies ({TAITT} 2026)",
month = jun,
year = "2026",
address = "Tilburg, the Netherlands",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2026.taitt-1.6/",
pages = "49--51",
abstract = "In this demo, we present COPECO-Speech, a multimodal post-editing workbench designed for translator training with AI-based translation technologies. It extends an existing pedagogical post-editing platform (COPECO) by integrating speech input and Large Language Model (LLM)-assisted editing. The workbench has different post-editing modalities and helps teachers annotate student tasks using either a shared or personalized annotation scheme. The system logs all interactions{---}including keystrokes, speech input, editing actions and LLM operations{---}enabling detailed analysis of post-editing processes."
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<abstract>In this demo, we present COPECO-Speech, a multimodal post-editing workbench designed for translator training with AI-based translation technologies. It extends an existing pedagogical post-editing platform (COPECO) by integrating speech input and Large Language Model (LLM)-assisted editing. The workbench has different post-editing modalities and helps teachers annotate student tasks using either a shared or personalized annotation scheme. The system logs all interactions—including keystrokes, speech input, editing actions and LLM operations—enabling detailed analysis of post-editing processes.</abstract>
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%0 Conference Proceedings
%T COPECO-Speech: Multimodal Post-Editing with Speech and LLMs for Translation Teaching
%A Liyanapathirana, Jeevanthi
%A Bouillon, Pierrette
%A Mutal, Jonathan
%A Girletti, Sabrina
%A Volkart, Lise
%Y Krüger, Ralph
%Y Kenny, Dorothy
%Y Castilho, Sheila
%Y Álvarez-Vidal, Sergi
%Y Aranberri, Nora
%Y Ginel, María Isabel Rivas
%Y Hackenbuchner, Janiça
%S Proceedings of the 1st International Workshop on Teaching AI-Based Translation and Technologies (TAITT 2026)
%D 2026
%8 June
%I European Association for Machine Translation
%C Tilburg, the Netherlands
%F liyanapathirana-etal-2026-copeco
%X In this demo, we present COPECO-Speech, a multimodal post-editing workbench designed for translator training with AI-based translation technologies. It extends an existing pedagogical post-editing platform (COPECO) by integrating speech input and Large Language Model (LLM)-assisted editing. The workbench has different post-editing modalities and helps teachers annotate student tasks using either a shared or personalized annotation scheme. The system logs all interactions—including keystrokes, speech input, editing actions and LLM operations—enabling detailed analysis of post-editing processes.
%U https://aclanthology.org/2026.taitt-1.6/
%P 49-51
Markdown (Informal)
[COPECO-Speech: Multimodal Post-Editing with Speech and LLMs for Translation Teaching](https://aclanthology.org/2026.taitt-1.6/) (Liyanapathirana et al., TAITT 2026)
ACL