P ro M ut: The Evolution of NMT Didactic Tools (2025)

Abstract: Neural Machine Translation intensifies educational challenges in translation technologies. The MultiTraiNMT project developed MutNMT, an open-source, didactic platform for training and evaluating NMT systems. Building upon it, LT-LiDER introduces ProMut which implements three main novel features: migration of the core NMT framework from JoeyNMT to MarianNMT, close integration with OPUS datasets, engines and connectors and the addition of a researcher profile for larger datasets and extended training processes and evaluation.

## introduction the integration of language and translation technologies into the education of future professionals has consistently posed significant challenges since these technologies first emerged. the advent of machine translation-especially with the rise of neural machine translation (nmt) systems-has added further layers of complexity, impacting both the training of students and the skill development of educators. these challenges continue to be highly relevant today. machine translation has become a cornerstone in the translation industry, driven by ongoing advancements that introduce new functionalities and refine existing systems. consequently, having access to up-to-date, well-maintained tools is crucial. such tools must not only clarify the workflows and tasks involved in incorporating neural machine translation into professional practice but also encourage meaningful interactions that enhance users' understanding of these systems. ## background within the broader context of rapid nmt adoption, the machine translation training for multilingual citizens project foot_0 was conceived to provide the resources needed for both trainers and students to effectively learn about and operate nmt systems. a central achievement of this project was the development of mutnmt, a platform enabling the management and creation of nmt engines. mutnmt also integrated features for evaluating translation quality, enhancing its applicability as both a training and research tool. as open-source software, mutnmt is freely accessible on github foot_1 alongside comprehensive documentation. additionally, it is hosted on the servers of the autonomous university of barcelona (uab), where it supports a community of over 700 registered users. mutnmt allows users to upload data corpora for training engines in any language combination. based on the joey nmt framework @xcite , it was developed specifically for pedagogical purposes, with limitations on the volume of training data and the complexity of the training process. once an engine is trained, it can be used directly within the platform for translation tasks. users can also leverage various metrics to evaluate translation quality or to compare results with other mt systems. building on this foundation, the lt-lider project foot_2 expanded the focus to include the development of digital literacy competencies among professionals, trainers, and trainees in translation and multilingual communication. one of its outputs is promut, a didactic tool aimed at enabling advanced engagement with and management of nmt systems. promut offers functionalities for creating engines and evaluating translation quality, while also broadening the system's capabilities and contexts of use. by deepening technical understanding and diversifying application scenarios, promut stands as a robust resource for education and training in translation technologies. ## from mutnmt to promut mutnmt is currently an application focused on teaching users of translation technologies the essentials about data management, training, usage and evaluation of machine translation systems. the online application implements different profiles with different rights regarding the ability to train a new engine within the tool. beginners are not allowed to do it, but they can interact with the rest of the functionality of the tool (see and upload datasets, see engine's training info, translate, inspect, evaluate). training, though, is only allowed to expert and admin profiles and is limited to the following parameters: in order to open up the use of mutnmt to a wider range of usages related with mt research, the lt-lider project generously expands the aforementioned limits through promut: promut, currently in internal testing by the lt-lider partners, will be available by may 2025 along with the code under a free/open-source licence.