Sergio Ortíz-Rojas

Also published as: Sergio Ortiz Rojas, Sergio Ortiz Rojas, Sergio Ortiz-Rojas


pdf bib
Bicleaner AI: Bicleaner Goes Neural
Jaume Zaragoza-Bernabeu | Gema Ramírez-Sánchez | Marta Bañón | Sergio Ortiz Rojas
Proceedings of the Thirteenth Language Resources and Evaluation Conference

This paper describes the experiments carried out during the development of the latest version of Bicleaner, named Bicleaner AI, a tool that aims at detecting noisy sentences in parallel corpora. The tool, which now implements a new neural classifier, uses state-of-the-art techniques based on pre-trained transformer-based language models fine-tuned on a binary classification task. After that, parallel corpus filtering is performed, discarding the sentences that have lower probability of being mutual translations. Our experiments, based on the training of neural machine translation (NMT) with corpora filtered using Bicleaner AI for two different scenarios, show significant improvements in translation quality compared to the previous version of the tool which implemented a classifier based on Extremely Randomized Trees.

pdf bib
Human evaluation of web-crawled parallel corpora for machine translation
Gema Ramírez-Sánchez | Marta Bañón | Jaume Zaragoza-Bernabeu | Sergio Ortiz Rojas
Proceedings of the 2nd Workshop on Human Evaluation of NLP Systems (HumEval)

Quality assessment has been an ongoing activity of the series of ParaCrawl efforts to crawl massive amounts of parallel data from multilingual websites for 29 languages. The goal of ParaCrawl is to get parallel data that is good for machine translation. To prove so, both, automatic (extrinsic) and human (intrinsic and extrinsic) evaluation tasks have been included as part of the quality assessment activity of the project. We sum up the various methods followed to address these evaluation tasks for the web-crawled corpora produced and their results. We review their advantages and disadvantages for the final goal of the ParaCrawl project and the related ongoing project MaCoCu.


pdf bib
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.

pdf bib
Bifixer and Bicleaner: two open-source tools to clean your parallel data
Gema Ramírez-Sánchez | Jaume Zaragoza-Bernabeu | Marta Bañón | Sergio Ortiz Rojas
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

This paper shows the utility of two open-source tools designed for parallel data cleaning: Bifixer and Bicleaner. Already used to clean highly noisy parallel content from crawled multilingual websites, we evaluate their performance in a different scenario: cleaning publicly available corpora commonly used to train machine translation systems. We choose four English–Portuguese corpora which we plan to use internally to compute paraphrases at a later stage. We clean the four corpora using both tools, which are described in detail, and analyse the effect of some of the cleaning steps on them. We then compare machine translation training times and quality before and after cleaning these corpora, showing a positive impact particularly for the noisiest ones.


pdf bib
Prompsit’s submission to WMT 2018 Parallel Corpus Filtering shared task
Víctor M. Sánchez-Cartagena | Marta Bañón | Sergio Ortiz-Rojas | Gema Ramírez
Proceedings of the Third Conference on Machine Translation: Shared Task Papers

This paper describes Prompsit Language Engineering’s submissions to the WMT 2018 parallel corpus filtering shared task. Our four submissions were based on an automatic classifier for identifying pairs of sentences that are mutual translations. A set of hand-crafted hard rules for discarding sentences with evident flaws were applied before the classifier. We explored different strategies for achieving a training corpus with diverse vocabulary and fluent sentences: language model scoring, an active-learning-inspired data selection algorithm and n-gram saturation. Our submissions were very competitive in comparison with other participants on the 100 million word training corpus.


pdf bib
Abu-MaTran: automatic building of machine translation
Antonio Toral | Sergio Ortiz Rojas | Mikel Forcada | Nikola Lubesic | Prokopis Prokopidis
Proceedings of the 19th Annual Conference of the European Association for Machine Translation: Projects/Products

pdf bib
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.

pdf bib
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


pdf bib
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

pdf bib
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

pdf bib
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


pdf bib
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.

pdf bib
Abu-MaTran at WMT 2014 Translation Task: Two-step Data Selection and RBMT-Style Synthetic Rules
Raphael Rubino | Antonio Toral | Victor M. Sánchez-Cartagena | Jorge Ferrández-Tordera | Sergio Ortiz-Rojas | Gema Ramírez-Sánchez | Felipe Sánchez-Martínez | Andy Way
Proceedings of the Ninth Workshop on Statistical Machine Translation


pdf bib
Opinum: statistical sentiment analysis for opinion classification
Boyan Bonev | Gema Ramírez-Sánchez | Sergio Ortiz Rojas
Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis


pdf bib
Joint efforts to further develop and incorporate Apertium into the document management flow at Universitat Oberta de Catalunya
Luis Villarejo Muñoz | Sergio Ortiz Rojas | Mireia Ginestí Rosell
Proceedings of the First International Workshop on Free/Open-Source Rule-Based Machine Translation

This article describes the needs of UOC regarding translation and how these needs are satisfied by Prompsit further developing a free rule-based machine translation system: Apertium. We initially describe the general framework regarding linguistic needs inside UOC. Then, section 2 introduces Apertium and outlines the development scenario that Prompsit executed. After that, section 3 outlines the specific needs of UOC and why Apertium was chosen as the machine translation engine. Then, section 4 describes some of the features specially developed in this project. Section 5 explains how the linguistic data was improved to increase the quality of the output in Catalan and Spanish. And, finally, we draw conclusions and outline further work originating from the project.


pdf bib
An open-source shallow-transfer machine translation engine for the Romance languages of Spain
Antonio M. Corbi-Bellot | Mikel L. Forcada | Sergio Ortíz-Rojas | Juan Antonio Pérez-Ortiz | Gema Ramírez-Sánchez | Felipe Sánchez-Martínez | Iñaki Alegria | Aingeru Mayor | Kepa Sarasola
Proceedings of the 10th EAMT Conference: Practical applications of machine translation

pdf bib
An Open Architecture for Transfer-based Machine Translation between Spanish and Basque
Iñaki Alegria | Arantza Diaz de Ilarraza | Gorka Labaka | Mikel Lersundi | Aingeru Mayor | Kepa Sarasola | Mikel L. Forcada | Sergio Ortiz-Rojas | Lluís Padró
Workshop on open-source machine translation

We present the current status of development of an open architecture for the translation from Spanish into Basque. The machine translation architecture uses an open source analyser for Spanish and new modules mainly based on finite-state transducers. The project is integrated in the OpenTrad initiative, a larger government funded project shared among different universities and small companies, which will also include MT engines for translation among the main languages in Spain. The main objective is the construction of an open, reusable and interoperable framework. This paper describes the design of the engine, the formats it uses for the communication among the modules, the modules reused from other project named Matxin and the new modules we are building.

pdf bib
An Open-Source Shallow-Transfer Machine Translation Toolbox: Consequences of Its Release and Availability
Carme Armentano-Oller | Antonio M. Corbí-Bellot | Mikel L. Forcada | Mireia Ginestí-Rosell | Boyan Bonev | Sergio Ortiz-Rojas | Juan Antonio Pérez-Ortiz | Gema Ramírez-Sánchez | Felipe Sánchez-Martínez
Workshop on open-source machine translation

By the time Machine Translation Summit X is held in September 2005, our group will have released an open-source machine translation toolbox as part of a large government-funded project involving four universities and three linguistic technology companies from Spain. The machine translation toolbox, which will most likely be released under a GPL-like license includes (a) the open-source engine itself, a modular shallow-transfer machine translation engine suitable for related languages and largely based upon that of systems we have already developed, such as interNOSTRUM for Spanish—Catalan and Traductor Universia for Spanish—Portuguese, (b) extensive documentation (including document type declarations) specifying the XML format of all linguistic (dictionaries, rules) and document format management files, (c) compilers converting these data into the high-speed (tens of thousands of words a second) format used by the engine, and (d) pilot linguistic data for Spanish—Catalan and Spanish—Galician and format management specifications for the HTML, RTF and plain text formats. After describing very briefly this toolbox, this paper aims at exploring possible consequences of the availability of this architecture, including the community-driven development of machine translation systems for languages lacking this kind of linguistic technology.