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ALBAYZIN Query-by-example Spoken Term Detection 2016 evaluation
dc.contributor.author | Tejedor, Javier | |
dc.contributor.author | Toledano, Doroteo T. | |
dc.contributor.author | López-Otero, Paula | |
dc.contributor.author | Docío-Fernández, Laura | |
dc.contributor.author | Proença, Jorge | |
dc.contributor.author | Perdigão, Fernando | |
dc.contributor.author | García-Granada, Fernando | |
dc.contributor.author | Sanchis, Emilio | |
dc.contributor.author | Pompili, Anna | |
dc.contributor.author | Abad, Alberto | |
dc.date.accessioned | 2024-07-02T17:37:28Z | |
dc.date.available | 2024-07-02T17:37:28Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Tejedor, J., Toledano, D., Lopez-Otero, P. et al. ALBAYZIN Query-by-example Spoken Term Detection 2016 evaluation. J AUDIO SPEECH MUSIC PROC. 2018, 2 (2018). https://doi.org/10.1186/s13636-018-0125-9 | es_ES |
dc.identifier.issn | 1687-4722 | |
dc.identifier.uri | http://hdl.handle.net/2183/37657 | |
dc.description.abstract | [Abstract]: Query-by-example Spoken Term Detection (QbE STD) aims to retrieve data from a speech repository given an acoustic (spoken) query containing the term of interest as the input. This paper presents the systems submitted to the ALBAYZIN QbE STD 2016 Evaluation held as a part of the ALBAYZIN 2016 Evaluation Campaign at the IberSPEECH 2016 conference. Special attention was given to the evaluation design so that a thorough post-analysis of the main results could be carried out. Two different Spanish speech databases, which cover different acoustic and language domains, were used in the evaluation: the MAVIR database, which consists of a set of talks from workshops, and the EPIC database, which consists of a set of European Parliament sessions in Spanish. We present the evaluation design, both databases, the evaluation metric, the systems submitted to the evaluation, the results, and a thorough analysis and discussion. Four different research groups participated in the evaluation, and a total of eight template matching-based systems were submitted. We compare the systems submitted to the evaluation and make an in-depth analysis based on some properties of the spoken queries, such as query length, single-word/multi-word queries, and in-language/out-of-language queries. | es_ES |
dc.description.sponsorship | This work was partially supported by Fundação para a Ciência e Tecnologia (FCT) under the projects UID/EEA/50008/2013 (pluriannual funding in the scope of the LETSREAD project) and UID/CEC/50021/2013, and Grant SFRH/BD/97187/2013. Jorge Proença is supported by the SFRH/BD/97204/2013 FCT Grant. This work was also supported by the Galician Government (‘Centro singular de investigación de Galicia’ accreditation 2016-2019 ED431G/01 and the research contract GRC2014/024 (Modalidade: Grupos de Referencia Competitiva 2014)), the European Regional Development Fund (ERDF), the projects “DSSL: Redes Profundas y Modelos de Subespacios para Detección y Seguimiento de Locutor, Idioma y Enfermedades Degenerativas a partir de la Voz” (TEC2015-68172-C2-1-P) and the TIN2015-64282-R funded by Ministerio de Economía y Competitividad in Spain, the Spanish Government through the project "TraceThem" (TEC2015-65345-P), and AtlantTIC ED431G/04. | es_ES |
dc.description.sponsorship | Portugal. Fundação para a Ciência e a Tecnologia; UID/EEA/50008/2013 | es_ES |
dc.description.sponsorship | Portugal. Fundação para a Ciência e a Tecnologia; UID/CEC/50021/2013 | es_ES |
dc.description.sponsorship | Portugal. Fundação para a Ciência e a Tecnologia; SFRH/BD/97187/2013 | es_ES |
dc.description.sponsorship | Portugal. Fundação para a Ciência e a Tecnologia; SFRH/BD/97204/2013 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G/01 | es_ES |
dc.description.sponsorship | Xunta de Galicia; GRC2014/024 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G/04 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | SpringerOpen & European Association for Signal Processing | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TEC2015-68172-C2-1-P/ES/REDES PROFUNDAS Y MODELOS DE SUBESPACIOS PARA DETECCION Y SEGUIMIENTO DE LOCUTOR, IDIOMA Y ENFERMEDADES DEGENERATIVAS A PARTIR DE LA VOZ | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2015-64282-R/ES/MODELOS DE LENGUAJE PROBABILISTICOS PARA RANKINGS PERSONALIZADOS EN SISTEMAS DE ACCESO A LA INFORMACION | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TEC2015-65345-P/ES/DETECCION MULTIMEDIA Y MULTILINGUE DE INFORMACION SOBRE PERSONAS | es_ES |
dc.relation.uri | https://doi.org/10.1186/s13636-018-0125-9 | es_ES |
dc.rights | Atribución 4.0 Internacional | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Query-by-example Spoken Term Detection | es_ES |
dc.subject | International evaluation | es_ES |
dc.subject | Spanish | es_ES |
dc.subject | Search on spontaneous speech | es_ES |
dc.title | ALBAYZIN Query-by-example Spoken Term Detection 2016 evaluation | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | EURASIP Journal on Audio, Speech, and Music Processing | es_ES |
UDC.issue | 2 | es_ES |
UDC.startPage | 1 | es_ES |
UDC.endPage | 25 | es_ES |
dc.identifier.doi | 10.1186/s13636-018-0125-9 |
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