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20162023
most citedOnline Learning for Neural Machine Translation Post-editing

25 citations · 76 across the 12 of their papers we have counts for

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Showing cs.CLShow all

13 papers · 1 filter

cs.CL2023

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…

cs.CL2022

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…

cs.CL2021

Two Demonstrations of the Machine Translation Applications to Historical Documents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We present our demonstration of two machine translation applications to historical documents. The first task consists in generating a new version of a historical document, written…

cs.CL2019★ 1 cited

An Interactive Machine Translation Framework for Modernizing Historical Documents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Due to the nature of human language, historical documents are hard to comprehend by contemporary people.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…

cs.CL2019★ 7 cited

Modernizing Historical Documents: a User Study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Accessibility to historical documents is mostly limited to scholars.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…

cs.CL2019

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…

cs.CL2019★ 11 cited

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…

cs.CL2019★ 2 cited

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…

cs.CL2018★ 17 cited

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…

cs.CL2018★ 13 cited

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…

cs.CL2018

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…

cs.CL2018

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…

cs.CL2016

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…