72 citations · 342 across the 17 of their papers we have counts for
17 papers · 1 filter
Automatic Discrimination of Human and Neural Machine Translation in Multilingual Scenarios
Malina Chichirau, Rik van Noord, Antonio Toral
We tackle the task of automatically discriminating between human and machine translations. As opposed to most previous work, we perform experiments in a multilingual setting, consi…
Unsupervised Translation of German--Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource Language
Lukas Edman, Ahmet Üstün, Antonio Toral +1
This paper describes the methods behind the systems submitted by the University of Groningen for the WMT 2021 Unsupervised Machine Translation task for German--Lower Sorbian (DE--D…
The Impact of Post-editing and Machine Translation on Creativity and Reading Experience
Ana Guerberof Arenas, Antonio Toral
This article presents the results of a study involving the translation of a fictional story from English into Catalan in three modalities: machine-translated (MT), post-edited (MTP…
Machine Translation of Novels in the Age of Transformer
Antonio Toral, Antoni Oliver, Pau Ribas Ballestín
In this chapter we build a machine translation (MT) system tailored to the literary domain, specifically to novels, based on the state-of-the-art architecture in neural MT (NMT), t…
Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERT
Rik van Noord, Antonio Toral, Johan Bos
We combine character-level and contextual language model representations to improve performance on Discourse Representation Structure parsing. Character representations can easily…
Fine-grained Human Evaluation of Transformer and Recurrent Approaches to Neural Machine Translation for English-to-Chinese
Yuying Ye, Antonio Toral
This research presents a fine-grained human evaluation to compare the Transformer and recurrent approaches to neural machine translation (MT), on the translation direction English-…
Reassessing Claims of Human Parity and Super-Human Performance in Machine Translation at WMT 2019
Antonio Toral
We reassess the claims of human parity and super-human performance made at the news shared task of WMT 2019 for three translation directions: English-to-German, English-to-Russian…
A Set of Recommendations for Assessing Human-Machine Parity in Language Translation
Samuel Läubli, Sheila Castilho, Graham Neubig +3
The quality of machine translation has increased remarkably over the past years, to the degree that it was found to be indistinguishable from professional human translation in a nu…
Post-editese: an Exacerbated Translationese
Antonio Toral
Post-editing (PE) machine translation (MT) is widely used for dissemination because it leads to higher productivity than human translation from scratch (HT). In addition, PE transl…
The Effect of Translationese in Machine Translation Test Sets
Mike Zhang, Antonio Toral
The effect of translationese has been studied in the field of machine translation (MT), mostly with respect to training data. We study in depth the effect of translationese on test…
Exploring Neural Methods for Parsing Discourse Representation Structures
Rik van Noord, Lasha Abzianidze, Antonio Toral +1
Neural methods have had several recent successes in semantic parsing, though they have yet to face the challenge of producing meaning representations based on formal semantics. We…
Attaining the Unattainable? Reassessing Claims of Human Parity in Neural Machine Translation
Antonio Toral, Sheila Castilho, Ke Hu +1
We reassess a recent study (Hassan et al., 2018) that claimed that machine translation (MT) has reached human parity for the translation of news from Chinese into English, using pa…
Quantitative Fine-Grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian
Filip Klubička, Antonio Toral, Víctor M. Sánchez-Cartagena
This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-establ…
What Level of Quality can Neural Machine Translation Attain on Literary Text?
Antonio Toral, Andy Way
Given the rise of a new approach to MT, Neural MT (NMT), and its promising performance on different text types, we assess the translation quality it can attain on what is perceived…
Fine-grained human evaluation of neural versus phrase-based machine translation
Filip Klubička, Antonio Toral, Víctor M. Sánchez-Cartagena
We compare three approaches to statistical machine translation (pure phrase-based, factored phrase-based and neural) by performing a fine-grained manual evaluation via error annota…
A Multifaceted Evaluation of Neural versus Phrase-Based Machine Translation for 9 Language Directions
Antonio Toral, Víctor M. Sánchez-Cartagena
We aim to shed light on the strengths and weaknesses of the newly introduced neural machine translation paradigm. To that end, we conduct a multifaceted evaluation in which we comp…
Mining and Exploiting Domain-Specific Corpora in the PANACEA Platform
Núria Bel, Vassilis Papavasiliou, Prokopis Prokopidis +2
The objective of the PANACEA ICT-2007.2.2 EU project is to build a platform that automates the stages involved in the acquisition, production, updating and maintenance of the large…