Matteo Negri

Online Automatic Post-editing for MT in a Multi-Domain Translation Environment

2017

Rajen Chatterjee, Gebremedhen Gebremelak, Matteo Negri, Marco Turchi. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers. 2017.

Transfer Learning in Multilingual Neural Machine Translation with Dynamic Vocabulary

2018 · arXiv (Cornell University)

We propose a method to transfer knowledge across neural machine translation (NMT) models by means of a shared dynamic vocabulary. Our approach allows to extend an initial model for a given language pair to cover …

Machine Translation for Machines: the Sentiment Classification Use Case

2019 · arXiv (Cornell University)

We propose a neural machine translation (NMT) approach that, instead of pursuing adequacy and fluency ("human-oriented" quality criteria), aims to generate translations that are best suited as input to a natural language processing component designed …

On knowledge distillation for direct speech translation

2020 · Institutional Research Information System (Università degli Studi di Trento)

Direct speech translation (ST) has shown to be a complex task requiring knowledge transfer from its sub-tasks: automatic speech recognition (ASR) and machine translation (MT). For MT, one of the most promising techniques to transfer …

Cascade versus Direct Speech Translation: Do the Differences Still Make a Difference?

2021

Luisa Bentivogli, Mauro Cettolo, Marco Gaido, Alina Karakanta, Alberto Martinelli, Matteo Negri, Marco Turchi. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language …

Visualization: the missing factor in Simultaneous Speech Translation

2021 · arXiv (Cornell University)

Simultaneous speech translation (SimulST) is the task in which output generation has to be performed on partial, incremental speech input. In recent years, SimulST has become popular due to the spread of cross-lingual application scenarios, …

Mind the Inclusivity Gap: Multilingual Gender-Neutral Translation Evaluation with mGeNTE

2025

Beatrice Savoldi, Giuseppe Attanasio, Eleonora Cupin, Eleni Gkovedarou, Janiça Hackenbuchner, Anne Lauscher, Matteo Negri, Andrea Piergentili, Manjinder Thind, Luisa Bentivogli. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. 2025.

Findings of the 2015 Workshop on Statistical Machine Translation

2015

Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Barry Haddow, Matthias Huck, Chris Hokamp, Philipp Koehn, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Carolina Scarton, Lucia Specia, Marco Turchi. Proceedings of the Tenth Workshop on Statistical …

Findings of the 2016 Conference on Machine Translation

2016

Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Varvara Logacheva, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Martin Popel, Matt Post, Raphael Rubino, Carolina Scarton, …

Multi-Domain Neural Machine Translation through Unsupervised Adaptation

2017

We investigate the application of Neural Machine Translation (NMT) under the following three conditions posed by realworld application scenarios. First, we operate with an input stream of sentences coming from many different domains and with …

Findings of the 2017 Conference on Machine Translation (WMT17)

2017

Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Shujian Huang, Matthias Huck, Philipp Koehn, Qun Liu, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Raphael Rubino, Lucia Specia, Marco Turchi. Proceedings of the …

The IWSLT 2019 Evaluation Campaign

2019 · Research Publications (Maastricht University)

The IWSLT 2019 evaluation campaign featured three tasks: speech translation of (i) TED talks and (ii) How2 instructional videos from English into German and Portuguese, and (iii) text translation of TED talks from English into …