Search Results for author: Álvaro Peris

Found 13 papers, 10 papers with code

A User Study of the Incremental Learning in NMT

no code implementations EAMT 2020 Miguel Domingo, Mercedes García-Martínez, Álvaro Peris, Alexandre Helle, Amando Estela, Laurent Bié, Francisco Casacuberta, Manuel Herranz

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.

Incremental Learning Machine Translation +2

Interactive-predictive neural multimodal systems

no code implementations30 May 2019 Álvaro Peris, Francisco Casacuberta

We show that, following this framework, we approximately halve the effort spent for correcting the outputs generated by the automatic systems.

Machine Translation Translation +1

Active Learning for Interactive Neural Machine Translation of Data Streams

1 code implementation CONLL 2018 Álvaro Peris, Francisco Casacuberta

We study the application of active learning techniques to the translation of unbounded data streams via interactive neural machine translation.

Active Learning Machine Translation +1

NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning

1 code implementation9 Jul 2018 Álvaro Peris, Francisco Casacuberta

We present NMT-Keras, a flexible toolkit for training deep learning models, which puts a particular emphasis on the development of advanced applications of neural machine translation systems, such as interactive-predictive translation protocols and long-term adaptation of the translation system via continuous learning.

General Classification Machine Translation +6

Online Learning for Effort Reduction in Interactive Neural Machine Translation

1 code implementation10 Feb 2018 Álvaro Peris, Francisco Casacuberta

We show that a neural machine translation system can be rapidly adapted to a specific domain, exclusively by means of online learning techniques.

Machine Translation Translation

Egocentric Video Description based on Temporally-Linked Sequences

1 code implementation7 Apr 2017 Marc Bolaños, Álvaro Peris, Francisco Casacuberta, Sergi Soler, Petia Radeva

We propose a novel methodology that exploits information from temporally neighboring events, matching precisely the nature of egocentric sequences.

Video Description

Video Description using Bidirectional Recurrent Neural Networks

1 code implementation12 Apr 2016 Álvaro Peris, Marc Bolaños, Petia Radeva, Francisco Casacuberta

Although traditionally used in the machine translation field, the encoder-decoder framework has been recently applied for the generation of video and image descriptions.

Text Generation Translation +2

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