Add to ORKGIn this paper, we describe the TALP- UPC participation in the News Task for German-English and Finish-English. Our primary submission implements a fully character to character neural machine translation architecture with an additional rescoring of a n-best list of hypothesis us- ing a forced back-translation to the source sentence. This model gives consistent im- provements on different pairs of languages for the language direction with the low- est performance while keeping the qual- ity in the direction with the highest perfor- mance. Additional experiments are reported for multilingual character to character neural machine translation, phrase-based trans- lation and the additional Turkish-English language pair.Peer Reviewe
Neural machine translation is a new approach to machine translation that has shown the effective res...
We explore the application of neural language models to machine translation. We develop a new model ...
Neural Machine Translation (MT) has reached state-of-the-art results. However, one of the main chall...
In this article we describe the TALP-UPC research group participation in the WMT18 news shared trans...
Although the problem of similar language translation has been an area of research interest for many ...
n the last years, deep learning algorithms have highly revolutionized several areas including speech...
In the last years, deep learning algorithms have highly revolutionized several areas including speec...
Machine translation, the task of automatically translating text from one natural language into anoth...
We consider a low-resource translation task from Finnish into Northern Sámi. Collecting all availabl...
Ozdemir O, Akin ES, Velioglu R, Dalyan T. A comparative study of neural machine translation models f...
Although neural machine translation has become the mainstream method and paradigm in the current res...
© Springer International Publishing AG, part of Springer Nature 2018. Neural machine translation (NM...
Though early successes of Statistical Machine Translation (SMT) systems are attributed in part to th...
Introduction of deep neural networks to the machine translation research ameliorated conventional ma...
We describe the University of Edinburgh’s submissions to the WMT20 news translation shared task for ...
Neural machine translation is a new approach to machine translation that has shown the effective res...
We explore the application of neural language models to machine translation. We develop a new model ...
Neural Machine Translation (MT) has reached state-of-the-art results. However, one of the main chall...
In this article we describe the TALP-UPC research group participation in the WMT18 news shared trans...
Although the problem of similar language translation has been an area of research interest for many ...
n the last years, deep learning algorithms have highly revolutionized several areas including speech...
In the last years, deep learning algorithms have highly revolutionized several areas including speec...
Machine translation, the task of automatically translating text from one natural language into anoth...
We consider a low-resource translation task from Finnish into Northern Sámi. Collecting all availabl...
Ozdemir O, Akin ES, Velioglu R, Dalyan T. A comparative study of neural machine translation models f...
Although neural machine translation has become the mainstream method and paradigm in the current res...
© Springer International Publishing AG, part of Springer Nature 2018. Neural machine translation (NM...
Though early successes of Statistical Machine Translation (SMT) systems are attributed in part to th...
Introduction of deep neural networks to the machine translation research ameliorated conventional ma...
We describe the University of Edinburgh’s submissions to the WMT20 news translation shared task for ...
Neural machine translation is a new approach to machine translation that has shown the effective res...
We explore the application of neural language models to machine translation. We develop a new model ...
Neural Machine Translation (MT) has reached state-of-the-art results. However, one of the main chall...