Persona: Ros Muñoz, Salvador
Cargando...
Dirección de correo electrónico
ORCID
0000-0001-6330-4958
Fecha de nacimiento
Proyectos de investigación
Unidades organizativas
Puesto de trabajo
Apellidos
Ros Muñoz
Nombre de pila
Salvador
Nombre
6 resultados
Resultados de la búsqueda
Mostrando 1 - 6 de 6
Publicación Hispanic Medieval Tagger (HisMeTag): una aplicación web para el etiquetado de entidades en textos medievalesDíez Platas, María Luisa; González-Blanco García, Elena; Rio Riande, Gimena del; Tobarra Abad, María de los Llanos; Ros Muñoz, Salvador; Robles Gómez, Antonio; Caminero Herráez, Agustín CarlosHisMeTag permite localizar entidades nombradas en textos escritos en español medieval, mediante un proceso automático de reconocimiento de entidades nombradas (NER) y técnicas de PLN para el procesamiento lingüístico y la generación de las distintas variantes que existieron en la época medieval. Localiza, etiqueta términos conocidos y propone nuevos términos para su validación.Publicación A bridge too far for artificial intelligence?: Automatic classification of stanzas in Spanish poetry(Wiley, 2022) Pérez Pozo, Álvaro; Rosa, Javier de la; Ros Muñoz, Salvador; González Blanco, Elena; Hernández Lorenzo, Laura; Sisto, Mirella deThe rise in artificial intelligence and natural language processing techniques has increased considerably in the last few decades. Historically, the focus has been primarily on texts expressed in prose form, leaving mostly aside figurative or poetic expressions of language due to their rich semantics and syntactic complexity. The creation and analysis of poetry have been commonly carried out by hand, with a few computer-assisted approaches. In the Spanish context, the promise of machine learning is starting to pan out in specific tasks such as metrical annotation and syllabification. However, there is a task that remains unexplored and underdeveloped: stanza classification. This classification of the inner structures of verses in which a poem is built upon is an especially relevant task for poetry studies since it complements the structural information of a poem. In this work, we analyzed different computational approaches to stanza classification in the Spanish poetic tradition. These approaches show that this task continues to be hard for computers systems, both based on classical machine learning approaches as well as statistical language models and cannot compete with traditional computational paradigms based on the knowledge of experts.Publicación Rantanplan, Fast and Accurate Syllabification and Scansion of Spanish Poetry(Sociedad Española para el Procesamiento del Lenguaje Natural, 2020-09) Rosa, Javier de la; Pérez Pozo, Álvaro; Hernández Lorenzo, Laura; Ros Muñoz, Salvador; González Blanco, ElenaAutomated analysis of Spanish poetry corpora lacks the richness of tools available for English. The existing options suffer from a number of issues: are limited to fixed-metre hendecasyllabic verses, are not publicly available, the syllabification procedure underneath is not thoroughly tested, and their speed is questionable. This paper introduces new methods to alleviate these concerns. For syllabification, we contribute with our own method and manually crafted corpus. For scansion, our approach is based on a heuristic for the application of rhetorical figures that alter metrical length. Experimental evaluation shows that both fixed-metre and mixed-metre poetry can be successfully analyzed, producing metrical patterns more accurately (increasing accuracy by 2% and 15%, respectively), and at a fraction of the time other methods need (running at least 100 times faster).Publicación Transformers analyzing poetry: multilingual metrical pattern prediction with transfomer-based language models(Springer, 2023) Rosa, Javier de la; Pérez Pozo, Álvaro; Sisto, Mirella De; Hernández Lorenzo, Laura; Díaz Paredes, Aitor; Ros Muñoz, Salvador; González Blanco, ElenaThe splitting of words into stressed and unstressed syllables is the foundation for the scansion of poetry, a process that aims at determining the metrical pattern of a line of verse within a poem. Intricate language rules and their exceptions, as well as poetic licenses exerted by the authors, make calculating these patterns a nontrivial task. Some rhetorical devices shrink the metrical length, while others might extend it. This opens the door for interpretation and further complicates the creation of automated scansion algorithms useful for automatically analyzing corpora on a distant reading fashion. In this paper, we compare the automated metrical pattern identification systems available for Spanish, English, and German, against fine-tuned monolingual and multilingual language models trained on the same task. Despite being initially conceived as models suitable for semantic tasks, our results suggest that transformers-based models retain enough structural information to perform reasonably well for Spanish on a monolingual setting, and outperforms both for English and German when using a model trained on the three languages, showing evidence of the benefits of cross-lingual transfer between the languages.Publicación The Automatic Quantitative Metrical Analysis of Spanish Poetry with Rantanplan: A Preliminary Approach(ICL CAS, 2021) Hernández Lorenzo, Laura; Sisto, Mirella De; Pérez Pozo, Álvaro; Rosa, Javier de la; Ros Muñoz, Salvador; González Blanco, Elena; Plecháč, P.; Kolár, R.; Bories,A.; Říha, J.In this paper, we present a quantitative approach to Spanish poetry and versification based on the application of our own automatic metrical tool, Rantanplan, to the complete poetic works of four early modern Spanish poets. All of the poetry of these four representative authors—Garcilaso de la Vega (1503–1536), Fernando de Herrera (1534–1597), Luis de Góngora (1561–1627), and Lope de Vega (1562–1635)—was automatically processed and stress positions were extracted. Thanks to the development of a new stanza identification feature of Rantanplan, we were able to detect metrical structures as well. By completing a quantitative analysis of the stress positions, line lengths, and stanzas used by each author, we aim to model their complete metrical profiles.Publicación EVI-LINHD, a virtual research environment for the Spanish speaking community(Oxford University Press, 2017-12) González-Blanco García, Elena; Rio Riande, Gimena del; Díez Platas, María Luisa; Olmo, Álvaro del; Urízar, Miguel; Martínez Cantón, Clara Isabel; Ros Muñoz, Salvador; Pastor Vargas, Rafael; Robles Gómez, Antonio; Caminero Herráez, Agustín CarlosLaboratorio de Innovación en Humanidades Digitales (UNED) has developed Entorno Virtual de Investigación del Laboratorio de Innovación en Humanidades Digitales (EVI-LINHD), the first virtual research environment devoted mainly to Spanish speakers interested in digital scholarly edition. EVI-LINHD combines different open-source software for developing a complete digital project: (1) a Webbased application markup tool—TEIscribe—combined with an eXistdb solution and a TEIPublisher platform, (2) Omeka for digital libraries, and (3) WordPress for simple Web pages. All these instances are linked to a local installation of the LINDAT/Common Language Resources and Technology Infrastructure (CLARIN) digital repository. LINDAT/CLARIN allows EVI-LINHD users to have their projects deposited and stored safely. Thanks to this solution, EVI-LINHD projects also improve their visibility. The specific metadata profile used in the repository is based on Dublin Core, and it is enriched with the Spanish translation of DARIAH’s Taxonomy of Digital Research Activities in the Humanities.