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dc.creatorRuiz Blais, Sebastián
dc.creatorCamacho Lozano, Arturo
dc.creatorFonseca Solís, Juan Manuel
dc.date.accessioned2019-09-06T14:44:56Z
dc.date.available2019-09-06T14:44:56Z
dc.date.issued2018
dc.identifier.citationhttps://asa.scitation.org/doi/10.1121/2.0000675es_ES
dc.identifier.issn1939-800X
dc.identifier.urihttp://hdl.handle.net/10669/79014
dc.description.abstractAccessible pedestrian signals (APS) enhance accessibility in streets around the world. Recent attempts to extend the use of APS to people with visual and audible impairments have emerged from the area of audio signal processing. Even though few authors have studied the detection of APS by sound, comprehensive literature in Biology has been published to detect other simple sounds like birds and frogs calls. Since these calls exhibit the same periodic and modulated nature as APS, many of these approaches can be adapted for this purpose. We present an algorithm that follows this approach. The algorithm was evaluated using a collection of 79 recordings gathered from streets in San Jose, Costa Rica, where an APS system will be implemented. Three types of sounds were available: low-pitch chirps, high-pitch chirps and cuckoo-like sounds. The results showed 91% precision, 80% recall, 83% F-measure, and 90% specificity.es_ES
dc.language.isoen_USes_ES
dc.sourceProceedings of Meetings on Acoustics, vol.30(1), pp.1-14es_ES
dc.subjectAccessible pedestrian signalses_ES
dc.titleAutomatic recognition of accessible pedestrian signalses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doi10.1121/2.0000675
dc.description.procedenceUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ingeniería::Centro de Investigaciones en Tecnologías de Información y Comunicación (CITIC)es_ES
dc.description.procedenceUCR::Vicerrectoría de Docencia::Ingeniería::Facultad de Ingeniería::Escuela de Ciencias de la Computación e Informáticaes_ES


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