25 citations · 76 across the 12 of their papers we have counts for
18 papers
AutoNMT: A Framework to Streamline the Research of Seq2Seq Models
Salvador Carrión, Francisco Casacuberta
We present AutoNMT, a framework to streamline the research of seq-to-seq models by automating the data pipeline (i.e., file management, data preprocessing, and exploratory analysis…
Findings of the Covid-19 MLIA Machine Translation Task
Francisco Casacuberta, Alexandru Ceausu, Khalid Choukri +10
This work presents the results of the machine translation (MT) task from the Covid-19 MLIA @ Eval initiative, a community effort to improve the generation of MT systems focused on…
Two Demonstrations of the Machine Translation Applications to Historical Documents
Miguel Domingo, Francisco Casacuberta
We present our demonstration of two machine translation applications to historical documents. The first task consists in generating a new version of a historical document, written…
An Interactive Machine Translation Framework for Modernizing Historical Documents
Miguel Domingo, Francisco Casacuberta
Due to the nature of human language, historical documents are hard to comprehend by contemporary people. This limits their accessibility to scholars specialized in the time period…
Modernizing Historical Documents: a User Study
Miguel Domingo, Francisco Casacuberta
Accessibility to historical documents is mostly limited to scholars. This is due to the language barrier inherent in human language and the linguistic properties of these documents…
Demonstration of a Neural Machine Translation System with Online Learning for Translators
Miguel Domingo, Mercedes García-Martínez, Amando Estela +5
We introduce a demonstration of our system, which implements online learning for neural machine translation in a production environment. These techniques allow the system to contin…
Incremental Adaptation of NMT for Professional Post-editors: A User Study
Miguel Domingo, Mercedes García-Martínez, Álvaro Peris +5
A common use of machine translation in the industry is providing initial translation hypotheses, which are later supervised and post-edited by a human expert. During this revision…
Interactive-predictive neural multimodal systems
Álvaro Peris, Francisco Casacuberta
Despite the advances achieved by neural models in sequence to sequence learning, exploited in a variety of tasks, they still make errors. In many use cases, these are corrected by…
A Neural, Interactive-predictive System for Multimodal Sequence to Sequence Tasks
Álvaro Peris, Francisco Casacuberta
We present a demonstration of a neural interactive-predictive system for tackling multimodal sequence to sequence tasks. The system generates text predictions to different sequence…
How Much Does Tokenization Affect Neural Machine Translation?
Miguel Domingo, Mercedes Garcıa-Martınez, Alexandre Helle +2
Tokenization or segmentation is a wide concept that covers simple processes such as separating punctuation from words, or more sophisticated processes such as applying morphologica…
NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning
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 translati…
Active Learning for Interactive Neural Machine Translation of Data Streams
Álvaro Peris, Francisco Casacuberta
We study the application of active learning techniques to the translation of unbounded data streams via interactive neural machine translation. The main idea is to select, from an…
Online Learning for Effort Reduction in Interactive Neural Machine Translation
Álvaro Peris, Francisco Casacuberta
Neural machine translation systems require large amounts of training data and resources. Even with this, the quality of the translations may be insufficient for some users or domai…
Online Learning for Neural Machine Translation Post-editing
Álvaro Peris, Luis Cebrián, Francisco Casacuberta
Neural machine translation has meant a revolution of the field. Nevertheless, post-editing the outputs of the system is mandatory for tasks requiring high translation quality. Post…
Egocentric Video Description based on Temporally-Linked Sequences
Marc Bolaños, Álvaro Peris, Francisco Casacuberta +2
Egocentric vision consists in acquiring images along the day from a first person point-of-view using wearable cameras. The automatic analysis of this information allows to discover…
Neural Networks Classifier for Data Selection in Statistical Machine Translation
Álvaro Peris, Mara Chinea-Rios, Francisco Casacuberta
We address the data selection problem in statistical machine translation (SMT) as a classification task. The new data selection method is based on a neural network classifier. We p…
VIBIKNet: Visual Bidirectional Kernelized Network for Visual Question Answering
Marc Bolaños, Álvaro Peris, Francisco Casacuberta +1
In this paper, we address the problem of visual question answering by proposing a novel model, called VIBIKNet. Our model is based on integrating Kernelized Convolutional Neural Ne…
Video Description using Bidirectional Recurrent Neural Networks
Álvaro Peris, Marc Bolaños, Petia Radeva +1
Although traditionally used in the machine translation field, the encoder-decoder framework has been recently applied for the generation of video and image descriptions. The combin…