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The version of record of this article, first published in [Journal name], is available online at Publisher’s website: http://dx.doi.org/10.1186/s13636-018-0125-9Query-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 queriesAcknowledgements
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
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