Daniel Torregrosa


2019

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Leveraging Rule-Based Machine Translation Knowledge for Under-Resourced Neural Machine Translation Models
Daniel Torregrosa | Nivranshu Pasricha | Maraim Masoud | Bharathi Raja Chakravarthi | Juan Alonso | Noe Casas | Mihael Arcan
Proceedings of Machine Translation Summit XVII Volume 2: Translator, Project and User Tracks

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Proceedings of the Second Workshop on Multilingualism at the Intersection of Knowledge Bases and Machine Translation
Mihael Arcan | Marco Turchi | Jinhua Du | Dimitar Shterionov | Daniel Torregrosa
Proceedings of the Second Workshop on Multilingualism at the Intersection of Knowledge Bases and Machine Translation

2018

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Fast Neural Machine Translation Implementation
Hieu Hoang | Tomasz Dwojak | Rihards Krislauks | Daniel Torregrosa | Kenneth Heafield
Proceedings of the 2nd Workshop on Neural Machine Translation and Generation

This paper describes the submissions to the efficiency track for GPUs at the Workshop for Neural Machine Translation and Generation by members of the University of Edinburgh, Adam Mickiewicz University, Tilde and University of Alicante. We focus on efficient implementation of the recurrent deep-learning model as implemented in Amun, the fast inference engine for neural machine translation. We improve the performance with an efficient mini-batching algorithm, and by fusing the softmax operation with the k-best extraction algorithm. Submissions using Amun were first, second and third fastest in the GPU efficiency track.

2014

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Black-box integration of heterogeneous bilingual resources into an interactive translation system
Juan Antonio Pérez-Ortiz | Daniel Torregrosa | Mikel Forcada
Proceedings of the EACL 2014 Workshop on Humans and Computer-assisted Translation