Joan-Andreu Sánchez

Also published as: Joan Andreu Sánchez, Joan-Andreu Sanchez


2018

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On the Derivational Entropy of Left-to-Right Probabilistic Finite-State Automata and Hidden Markov Models
Joan Andreu Sánchez | Martha Alicia Rocha | Verónica Romero | Mauricio Villegas
Computational Linguistics, Volume 44, Issue 1 - April 2018

Probabilistic finite-state automata are a formalism that is widely used in many problems of automatic speech recognition and natural language processing. Probabilistic finite-state automata are closely related to other finite-state models as weighted finite-state automata, word lattices, and hidden Markov models. Therefore, they share many similar properties and problems. Entropy measures of finite-state models have been investigated in the past in order to study the information capacity of these models. The derivational entropy quantifies the uncertainty that the model has about the probability distribution it represents. The derivational entropy in a finite-state automaton is computed from the probability that is accumulated in all of its individual state sequences. The computation of the entropy from a weighted finite-state automaton requires a normalized model. This article studies an efficient computation of the derivational entropy of left-to-right probabilistic finite-state automata, and it introduces an efficient algorithm for normalizing weighted finite-state automata. The efficient computation of the derivational entropy is also extended to continuous hidden Markov models.

2013

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Towards the Supervised Machine Translation: Real Word Alignments and Translations in a Multi-task Active Learning process
Martha-Alicia Rocha | Joan-Andreu Sanchez
Proceedings of Machine Translation Summit XIV: Posters

2011

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Handwritten Text Recognition for Historical Documents
Verónica Romero | Nicolás Serrano | Alejandro H. Toselli | Joan Andreu Sánchez | Enrique Vidal
Proceedings of the Workshop on Language Technologies for Digital Humanities and Cultural Heritage

2010

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UPV-PRHLT English–Spanish System for WMT10
Germán Sanchis-Trilles | Jesús Andrés-Ferrer | Guillem Gascó | Jesús González-Rubio | Pascual Martínez-Gómez | Martha-Alicia Rocha | Joan-Andreu Sánchez | Francisco Casacuberta
Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR

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The UPV-PRHLT Combination System for WMT 2010
Jesús González-Rubio | Germán Sanchis-Trilles | Joan-Andreu Sánchez | Jesús Andrés-Ferrer | Guillem Gascó | Pascual Martínez-Gómez | Martha-Alicia Rocha | Francisco Casacuberta
Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR

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ITI-UPV machine translation system for IWSLT 2010
Guillem Gascó | Vicent Alabau | Jesús-Andrés Ferrer | Jesús González-Rubio | Martha-Alicia Rocha | Germán Sanchis-Trilles | Francisco Casacuberta | Jorge González | Joan-Andreu Sánchez
Proceedings of the 7th International Workshop on Spoken Language Translation: Evaluation Campaign

This paper presents the submissions of the PRHLT group for the evaluation campaign of the International Workshop on Spoken Language Translation. We focus on the development of reliable translation systems between syntactically different languages (DIALOG task) and on the efficient training of SMT models in resource-rich scenarios (TALK task).

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Enlarged Search Space for SITG Parsing
Guillem Gascó | Joan-Andreu Sánchez | José-Miguel Benedí
Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics

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Interactive Predictive Parsing using a Web-based Architecture
Ricardo Sánchez-Sáez | Luis A. Leiva | Joan-Andreu Sánchez | José-Miguel Benedí
Proceedings of the NAACL HLT 2010 Demonstration Session

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Confidence Measures for Error Discrimination in an Interactive Predictive Parsing Framework
Ricardo Sánchez-Sáez | Joan Andreu Sánchez | José Miguel Benedí
Coling 2010: Posters

2009

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Interactive Predictive Parsing
Ricardo Sánchez-Sáez | Joan-Andreu Sánchez | José-Miguel Benedí
Proceedings of the 11th International Conference on Parsing Technologies (IWPT’09)

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Statistical Confidence Measures for Probabilistic Parsing
Ricardo Sánchez-Sáez | Joan-Andreu Sánchez | José-Miguel Benedí Ruíz
Proceedings of the International Conference RANLP-2009

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UPV translation system for IWSLT 2009
Guillem Gascó | Joan Andreu Sánchez
Proceedings of the 6th International Workshop on Spoken Language Translation: Evaluation Campaign

In this paper, we describe the machine translation system developed at the Polytechnic University of Valencia, which was used in our participation in the International Workshop on Spoken Language Translation (IWSLT) 2009. We have taken part only in the Chinese-English BTEC Task. In the evaluation campaign, we focused on the use of our hybrid translation system over the provided corpus and less effort was devoted to the use of preand post-processing techniques that could have improved the results. Our decoder is a hybrid machine translation system that combines phrase-based models together with syntax-based translation models. The syntactic formalism that underlies the whole decoding process is a Chomsky Normal Form Stochastic Inversion Transduction Grammar (SITG) with phrasal productions and a log-linear combination of probability models. The decoding algorithm is a CYK-like algorithm that combines the translated phrases inversely or directly in order to get a complete translation of the input sentence.

2008

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Using Parsed Corpora for Estimating Stochastic Inversion Transduction Grammars
Germán Sanchis | Joan Andreu Sánchez
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

An important problem when using Stochastic Inversion Transduction Grammars is their computational cost. More specifically, when dealing with corpora such as Europarl. only one iteration of the estimation algorithm becomes prohibitive. In this work, we apply a reduction of the cost by taking profit of the bracketing information in parsed corpora and show machine translation results obtained with a bracketed Europarl corpus, yielding interresting improvements when increasing the number of non-terminal symbols.

2006

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Stochastic Inversion Transduction Grammars for Obtaining Word Phrases for Phrase-based Statistical Machine Translation
Joan Andreu Sánchez | José Miguel Benedí
Proceedings on the Workshop on Statistical Machine Translation

2000

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Combination of N-Grams and Stochastic Context-Free Grammars for Language Modeling
Jose-Miguel Benedi | Joan-Andreu Sanchez
COLING 2000 Volume 1: The 18th International Conference on Computational Linguistics