Abstract
Despite the increasingly good quality of Machine Translation (MT) systems, MT outputs require corrections. Automatic Post-Editing (APE) models have been introduced to perform these corrections without human intervention. However, no system has been able to fully automate the Post-Editing (PE) process. Moreover, while numerous translation tools, such as Translation Memories (TMs), largely benefit from translators’ input, Human-Computer Interaction (HCI) remains limited when it comes to PE. This research-in-progress paper discusses APE models and suggests that they could be improved in more interactive scenarios, as previously done in MT with the creation of Interactive MT (IMT) systems. Based on the hypothesis that PE would benefit from HCI, two methodologies are proposed. Both suggest that traditional batch learning settings are not optimal for PE. Instead, online techniques are recommended to train and update PE models on the fly, via either real or simulated interactions with the translator.- Anthology ID:
- 2021.triton-1.19
- Volume:
- Proceedings of the Translation and Interpreting Technology Online Conference
- Month:
- July
- Year:
- 2021
- Address:
- Held Online
- Editors:
- Ruslan Mitkov, Vilelmini Sosoni, Julie Christine Giguère, Elena Murgolo, Elizabeth Deysel
- Venue:
- TRITON
- SIG:
- Publisher:
- INCOMA Ltd.
- Note:
- Pages:
- 167–173
- Language:
- URL:
- https://aclanthology.org/2021.triton-1.19
- DOI:
- Cite (ACL):
- Marie Escribe and Ruslan Mitkov. 2021. Interactive Models for Post-Editing. In Proceedings of the Translation and Interpreting Technology Online Conference, pages 167–173, Held Online. INCOMA Ltd..
- Cite (Informal):
- Interactive Models for Post-Editing (Escribe & Mitkov, TRITON 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2021.triton-1.19.pdf
- Data
- eSCAPE