Maria Fuentes

Also published as: Maria Fuentes Fort


pdf bib
UPC-CORE: What Can Machine Translation Evaluation Metrics and Wikipedia Do for Estimating Semantic Textual Similarity?
Alberto Barrón-Cedeño | Lluís Màrquez | Maria Fuentes | Horacio Rodríguez | Jordi Turmo
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity


pdf bib
Spell Checking in Spanish: The Case of Diacritic Accents
Jordi Atserias | Maria Fuentes | Rogelio Nazar | Irene Renau
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This article presents the problem of diacritic restoration (or diacritization) in the context of spell-checking, with the focus on an orthographically rich language such as Spanish. We argue that despite the large volume of work published on the topic of diacritization, currently available spell-checking tools have still not found a proper solution to the problem in those cases where both forms of a word are listed in the checker's dictionary. This is the case, for instance, when a word form exists with and without diacritics, such as continuo ‘continuous' and continuó ‘he/she/it continued', or when different diacritics make other word distinctions, as in continúo ‘I continue'. We propose a very simple solution based on a word bigram model derived from correctly typed Spanish texts and evaluate the ability of this model to restore diacritics in artificial as well as real errors. The case of diacritics is only meant to be an example of the possible applications for this idea, yet we believe that the same method could be applied to other kinds of orthographic or even grammatical errors. Moreover, given that no explicit linguistic knowledge is required, the proposed model can be used with other languages provided that a large normative corpus is available.

pdf bib
Summarizing a multimodal set of documents in a Smart Room
Maria Fuentes | Horacio Rodríguez | Jordi Turmo
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This article reports an intrinsic automatic summarization evaluation in the scientific lecture domain. The lecture takes place in a Smart Room that has access to different types of documents produced from different media. An evaluation framework is presented to analyze the performance of systems producing summaries answering a user need. Several ROUGE metrics are used and a manual content responsiveness evaluation was carried out in order to analyze the performance of the evaluated approaches. Various multilingual summarization approaches are analyzed showing that the use of different types of documents outperforms the use of transcripts. In fact, not using any part of the spontaneous speech transcription in the summary improves the performance of automatic summaries. Moreover, the use of semantic information represented in the different textual documents coming from different media helps to improve summary quality.


pdf bib
Support Vector Machines for Query-focused Summarization trained and evaluated on Pyramid data
Maria Fuentes | Enrique Alfonseca | Horacio Rodríguez
Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions


pdf bib
Re-using High-quality Resources for Continued Evaluation of Automated Summarization Systems
Laura Alonso | Maria Fuentes | Marc Massot | Horacio Rodríguez
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)


pdf bib
Cohesion and coherence for Automatic Summarization
Laura Alonso i Alemany | Maria Fuentes Fort
Student Research Workshop