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English-Russian Data Augmentation for Neural Machine Translation
In order to evaluate the quality of the NMT models, firstly, these models have been compared performing a quantitative analysis by means of several standard automatic metrics used in machine translation, and measuring the time spent and the amount of text generated for a good use in the language industry.
MAPA Project: Ready-to-Go Open-Source Datasets and Deep Learning Technology to Remove Identifying Information from Text Documents
This paper presents the outcomes of the MAPA project, a set of annotated corpora for 24 languages of the European Union and an open-source customisable toolkit able to detect and substitute sensitive information in text documents from any domain, using state-of-the art, deep learning-based named entity recognition techniques.
The Multilingual Anonymisation Toolkit for Public Administrations (MAPA) Project
We describe the MAPA project, funded under the Connecting Europe Facility programme, whose goal is the development of an open-source de-identification toolkit for all official European Union languages.
Europeana Translate: Providing multilingual access to digital cultural heritage
Europeana Translate is a project funded under the Connecting European Facility with the objective to take advantage of state-of-the-art machine translation in order to increase the multilinguality of resources in the cultural heritage domain
Neural Translation for the European Union (NTEU) Project
The Neural Translation for the European Union (NTEU) project aims to build a neural engine farm with all European official language combinations for eTranslation, without the necessity to use a high-resourced language as a pivot.
A User Study of the Incremental Learning in NMT
Adaptive neural machine translation systems, able to incrementally update the underlying models under an online learning regime, have been proven to be useful to improve the efficiency of this workflow.
Findings of the Covid-19 MLIA Machine Translation Task
This work presents the results of the machine translation (MT) task from the Covid-19 MLIA @ Eval initiative, a community effort to improve the generation of MT systems focused on the current Covid-19 crisis.
Eco.pangeamt: Industrializing Neural MT
Eco is Pangeanic{'}s customer portal for generic or specialized translation services (machine translation and post-editing, generic API MT and custom API MT).
Incremental Adaptation of NMT for Professional Post-editors: A User Study
A common use of machine translation in the industry is providing initial translation hypotheses, which are later supervised and post-edited by a human expert.
How Much Does Tokenization Affect Neural Machine Translation?
Separating punctuation and splitting tokens into words or subwords has proven to be helpful to reduce vocabulary and increase the number of examples of each word, improving the translation quality.
