Title
Design and evaluation of a voice-controlled elevator system to improve safety and accessibilityAuthor (from another institution)
xmlui.dri2xhtml.METS-1.0.item-contributorOtherinstitution
https://ror.org/0023sah13Version
http://purl.org/coar/version/c_ab4af688f83e57aa
Rights
© 2024 The AuthorsAccess
http://purl.org/coar/access_right/c_abf2Publisher’s version
https://doi.org/10.1109/OJIES.2024.3483552Published at
IEEE Open Journal of the Industrial Electronics Society Early AccessPublisher
IEEEKeywords
Speech recognition
Embedded systems
Human machine interaction
ODS 9 Industria, innovación e infraestructura ... [+]
Embedded systems
Human machine interaction
ODS 9 Industria, innovación e infraestructura ... [+]
Speech recognition
Embedded systems
Human machine interaction
ODS 9 Industria, innovación e infraestructura
ODS 10 Reducción de las desigualdades [-]
Embedded systems
Human machine interaction
ODS 9 Industria, innovación e infraestructura
ODS 10 Reducción de las desigualdades [-]
xmlui.dri2xhtml.METS-1.0.item-unesco-tesauro
http://vocabularies.unesco.org/thesaurus/mt5.40xmlui.dri2xhtml.METS-1.0.item-unesco-clasificacion
http://skos.um.es/unesco6/3304Abstract
This work introduces the design and assessment of a voice-controlled elevator system aimed at facilitating touchless interaction between users and hardware, thereby minimising contact and improving ac ... [+]
This work introduces the design and assessment of a voice-controlled elevator system aimed at facilitating touchless interaction between users and hardware, thereby minimising contact and improving accessibility for individuals with disabilities. The research distinguishes three distinct deployment scenarios – on cloud, on edge and embedded – with the ultimate goal of integrating the entire system into a low-resource environment on a custom carrier board. An objective evaluation measured acoustic conditions rigorously using a dataset of 2900 audio files recorded inside a laboratory elevator cabin featuring two internal coatings, five audio input devices, and under four distinct noise conditions. The study evaluated the performance of two Automatic Speech Recognition systems: Google's Speech-to-Text API and a Kaldi model adapted for this task, deployed using Vosk. Additionally, latency times for these transcribers and two communication protocols were measured to enhance efficiency. Finally, two subjective evaluations on clean and noisy conditions were conducted simulating a real world scenario. The results, yielding 84.7 and 77.2 points respectively in a System Usability Scale questionnaire, affirm the reliability of the presented prototype for industrial deployment. [-]
xmlui.dri2xhtml.METS-1.0.item-oaire-funderName
Gobierno Vascoxmlui.dri2xhtml.METS-1.0.item-oaire-fundingStream
Elkartek 2021xmlui.dri2xhtml.METS-1.0.item-oaire-awardNumber
KK-2021-00038xmlui.dri2xhtml.METS-1.0.item-oaire-awardURI
Sin informaciónxmlui.dri2xhtml.METS-1.0.item-oaire-awardTitle
Investigación en tecnologías de reconocimiento de voz para la interacción máquina-usuario (IVOZ)Collections
- Articles - Engineering [677]
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