Miquel Esplà-Gomis

Also published as: Miquel Esplà


2020

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ParaCrawl: Web-Scale Acquisition of Parallel Corpora
Marta Bañón | Pinzhen Chen | Barry Haddow | Kenneth Heafield | Hieu Hoang | Miquel Esplà-Gomis | Mikel L. Forcada | Amir Kamran | Faheem Kirefu | Philipp Koehn | Sergio Ortiz Rojas | Leopoldo Pla Sempere | Gema Ramírez-Sánchez | Elsa Sarrías | Marek Strelec | Brian Thompson | William Waites | Dion Wiggins | Jaume Zaragoza
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

We report on methods to create the largest publicly available parallel corpora by crawling the web, using open source software. We empirically compare alternative methods and publish benchmark data sets for sentence alignment and sentence pair filtering. We also describe the parallel corpora released and evaluate their quality and their usefulness to create machine translation systems.

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An English-Swahili parallel corpus and its use for neural machine translation in the news domain
Felipe Sánchez-Martínez | Víctor M. Sánchez-Cartagena | Juan Antonio Pérez-Ortiz | Mikel L. Forcada | Miquel Esplà-Gomis | Andrew Secker | Susie Coleman | Julie Wall
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

This paper describes our approach to create a neural machine translation system to translate between English and Swahili (both directions) in the news domain, as well as the process we followed to crawl the necessary parallel corpora from the Internet. We report the results of a pilot human evaluation performed by the news media organisations participating in the H2020 EU-funded project GoURMET.

2019

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ParaCrawl: Web-scale parallel corpora for the languages of the EU
Miquel Esplà | Mikel Forcada | Gema Ramírez-Sánchez | Hieu Hoang
Proceedings of Machine Translation Summit XVII Volume 2: Translator, Project and User Tracks

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Global Under-Resourced Media Translation (GoURMET)
Alexandra Birch | Barry Haddow | Ivan Tito | Antonio Valerio Miceli Barone | Rachel Bawden | Felipe Sánchez-Martínez | Mikel L. Forcada | Miquel Esplà-Gomis | Víctor Sánchez-Cartagena | Juan Antonio Pérez-Ortiz | Wilker Aziz | Andrew Secker | Peggy van der Kreeft
Proceedings of Machine Translation Summit XVII Volume 2: Translator, Project and User Tracks

2018

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UAlacant machine translation quality estimation at WMT 2018: a simple approach using phrase tables and feed-forward neural networks
Felipe Sánchez-Martínez | Miquel Esplà-Gomis | Mikel L. Forcada
Proceedings of the Third Conference on Machine Translation: Shared Task Papers

We describe the Universitat d’Alacant submissions to the word- and sentence-level machine translation (MT) quality estimation (QE) shared task at WMT 2018. Our approach to word-level MT QE builds on previous work to mark the words in the machine-translated sentence as OK or BAD, and is extended to determine if a word or sequence of words need to be inserted in the gap after each word. Our sentence-level submission simply uses the edit operations predicted by the word-level approach to approximate TER. The method presented ranked first in the sub-task of identifying insertions in gaps for three out of the six datasets, and second in the rest of them.

2016

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Producing Monolingual and Parallel Web Corpora at the Same Time - SpiderLing and Bitextor’s Love Affair
Nikola Ljubešić | Miquel Esplà-Gomis | Antonio Toral | Sergio Ortiz Rojas | Filip Klubička
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper presents an approach for building large monolingual corpora and, at the same time, extracting parallel data by crawling the top-level domain of a given language of interest. For gathering linguistically relevant data from top-level domains we use the SpiderLing crawler, modified to crawl data written in multiple languages. The output of this process is then fed to Bitextor, a tool for harvesting parallel data from a collection of documents. We call the system combining these two tools Spidextor, a blend of the names of its two crucial parts. We evaluate the described approach intrinsically by measuring the accuracy of the extracted bitexts from the Croatian top-level domain “.hr” and the Slovene top-level domain “.si”, and extrinsically on the English-Croatian language pair by comparing an SMT system built from the crawled data with third-party systems. We finally present parallel datasets collected with our approach for the English-Croatian, English-Finnish, English-Serbian and English-Slovene language pairs.

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Bitextor’s participation in WMT’16: shared task on document alignment
Miquel Esplà-Gomis | Mikel Forcada | Sergio Ortiz-Rojas | Jorge Ferrández-Tordera
Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers

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UAlacant word-level and phrase-level machine translation quality estimation systems at WMT 2016
Miquel Esplà-Gomis | Felipe Sánchez-Martínez | Mikel Forcada
Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers

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Stand-off Annotation of Web Content as a Legally Safer Alternative to Crawling for Distribution
Mikel L. Forcada | Miquel Esplà-Gomis | Juan Antonio Pérez-Ortiz
Proceedings of the 19th Annual Conference of the European Association for Machine Translation

2015

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Predicting Inflectional Paradigms and Lemmata of Unknown Words for Semi-automatic Expansion of Morphological Lexicons
Nikola Ljubešić | Miquel Esplà-Gomis | Filip Klubička | Nives Mikelić Preradović
Proceedings of the International Conference Recent Advances in Natural Language Processing

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Abu-MaTran: Automatic building of Machine Translation
Antonio Toral | Tommi A Pirinen | Andy Way | Gema Ramírez-Sánchez | Sergio Ortiz Rojas | Raphael Rubino | Miquel Esplà | Mikel Forcada | Vassilis Papavassiliou | Prokopis Prokopidis | Nikola Ljubešić
Proceedings of the 18th Annual Conference of the European Association for Machine Translation

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Abu-MaTran at WMT 2015 Translation Task: Morphological Segmentation and Web Crawling
Raphael Rubino | Tommi Pirinen | Miquel Esplà-Gomis | Nikola Ljubešić | Sergio Ortiz-Rojas | Vassilis Papavassiliou | Prokopis Prokopidis | Antonio Toral
Proceedings of the Tenth Workshop on Statistical Machine Translation

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UAlacant word-level machine translation quality estimation system at WMT 2015
Miquel Esplà-Gomis | Felipe Sánchez-Martínez | Mikel Forcada
Proceedings of the Tenth Workshop on Statistical Machine Translation

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Using on-line available sources of bilingual information for word-level machine translation quality estimation
Miquel Esplà-Gomis | Felipe Sánchez-Martínez | Mikel L. Forcada
Proceedings of the 18th Annual Conference of the European Association for Machine Translation

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Abu-MaTran: Automatic building of Machine Translation
Antonio Toral | Tommi A. Pirinen | Andy Way | Gema Ramírez-Sánchez | Sergio Ortiz Rojas | Raphael Rubino | Miquel Esplà | Mikel L. Forcada | Vassilis Papavassiliou | Prokopis Prokopidis | Nikola Ljubešić
Proceedings of the 18th Annual Conference of the European Association for Machine Translation

2014

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An efficient method to assist non-expert users in extending dictionaries by assigning stems and inflectional paradigms to unknknown words
Miquel Esplà-Gomis | Víctor M. Sánchez-Cartegna | Felipe Sánchez-Martínez | Rafael C. Carrasco | Mikel L. Forcada | Juan Antonio Pérez-Ortiz
Proceedings of the 17th Annual conference of the European Association for Machine Translation

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Extrinsic evaluation of web-crawlers in machine translation: a study on Croatian-English for the tourism domain
Antonio Toral | Raphael Rubino | Miquel Esplà-Gomis | Tommi Pirinen | Andy Way | Gema Ramírez-Sánchez
Proceedings of the 17th Annual conference of the European Association for Machine Translation

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Comparing two acquisition systems for automatically building an English—Croatian parallel corpus from multilingual websites
Miquel Esplà-Gomis | Filip Klubička | Nikola Ljubešić | Sergio Ortiz-Rojas | Vassilis Papavassiliou | Prokopis Prokopidis
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

In this paper we compare two tools for automatically harvesting bitexts from multilingual websites: bitextor and ILSP-FC. We used both tools for crawling 21 multilingual websites from the tourism domain to build a domain-specific English―Croatian parallel corpus. Different settings were tried for both tools and 10,662 unique document pairs were obtained. A sample of about 10% of them was manually examined and the success rate was computed on the collection of pairs of documents detected by each setting. We compare the performance of the settings and the amount of different corpora detected by each setting. In addition, we describe the resource obtained, both by the settings and through the human evaluation, which has been released as a high-quality parallel corpus.

2013

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Exploiting Qualitative Information from Automatic Word Alignment for Cross-lingual NLP Tasks
José G.C. de Souza | Miquel Esplà-Gomis | Marco Turchi | Matteo Negri
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2012

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UAlacant: Using Online Machine Translation for Cross-Lingual Textual Entailment
Miquel Esplà-Gomis | Felipe Sánchez-Martínez | Mikel L. Forcada
*SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012)

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Source-Language Dictionaries Help Non-Expert Users to Enlarge Target-Language Dictionaries for Machine Translation
Víctor M. Sánchez-Cartagena | Miquel Esplà-Gomis | Juan Antonio Pérez-Ortiz
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

In this paper, a previous work on the enlargement of monolingual dictionaries of rule-based machine translation systems by non-expert users is extended to tackle the complete task of adding both source-language and target-language words to the monolingual dictionaries and the bilingual dictionary. In the original method, users validate whether some suffix variations of the word to be inserted are correct in order to find the most appropriate inflection paradigm. This method is now improved by taking advantage from the strong correlation detected between paradigms in both languages to reduce the search space of the target-language paradigm once the source-language paradigm is known. Results show that, when the source-language word has already been inserted, the system is able to more accurately predict which is the right target-language paradigm, and the number of queries posed to users is significantly reduced. Experiments also show that, when the source language and the target language are not closely related, it is only the source-language part-of-speech category, but not the rest of information provided by the source-language paradigm, which helps to correctly classify the target-language word.

2011

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Enlarging Monolingual Dictionaries for Machine Translation with Active Learning and Non-Expert Users
Miquel Esplà-Gomis | Víctor M. Sánchez-Cartagena | Juan Antonio Pérez-Ortiz
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011

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Using word alignments to assist computer-aided translation users by marking which target-side words to change or keep unedited
Miquel Esplà | Felipe Sánchez-Martínez | Mikel L. Forcada
Proceedings of the 15th Annual conference of the European Association for Machine Translation