activity
20182026
most citedHow Much Does Tokenization Affect Neural Machine Translation?

17 citations · 36 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL2026

Comparative Evaluation of Machine Translation Systems on Images with Text

Blai Puchol, Sergio Gómez González, Miguel Domingo +1

This work presents a comparative evaluation of machine translation systems applied to images containing textual information, a task that lies at the intersection of computer vision…

cs.CL2026

DEEP: Docker-based Execution and Evaluation Platform

Sergio Gómez González, Miguel Domingo, Francisco Casacuberta

Comparative evaluation of several systems is a recurrent task in researching. It is a key step before deciding which system to use for our work, or, once our research has been cond…

cs.CL2025

Two Spelling Normalization Approaches Based on Large Language Models

Miguel Domingo, Francisco Casacuberta

The absence of standardized spelling conventions and the organic evolution of human language present an inherent linguistic challenge within historical documents, a longstanding co…

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Two Demonstrations of the Machine Translation Applications to Historical Documents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We present our demonstration of two machine translation applications to historical documents. The first task consists in generating a new version of a historical document, written…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An Interactive Machine Translation Framework for Modernizing Historical Documents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Due to the nature of human language, historical documents are hard to comprehend by contemporary people.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Modernizing Historical Documents: a User Study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Accessibility to historical documents is mostly limited to scholars.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.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…