Detection of speech events and speaker characteristics through photo-plethysmographic signal neural processing

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• dc.contributor.author Cámbara Ruiz, Guillermo
• dc.contributor.author Luque, Jordi
• dc.contributor.author Farrús, Mireia
• dc.date.accessioned 2020-05-07T08:00:59Z
• dc.date.issued 2020
• dc.description Comunicació presentada a: 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), celebrat de manera virtual a Barcelona del 4 al 8 de maig de 2020.
• dc.description.abstract The use of photoplethysmogram signal (PPG) for heart and sleep monitoring is commonly found nowadays in smart-phones and wrist wearables. Besides common usages, it has been proposed and reported that person information can be extracted from PPG for other uses, like biometry tasks. In this work, we explore several end-to-end convolutional neural network architectures for detection of human’s characteristics such as gender or person identity. In addition, we evaluate whether speech/non-speech events may be inferred from PPG signal, where speech might translate in fluctuations into the pulse signal. The obtained results are promising and clearly show the potential of fully end-to-end topologies for automatic extraction of meaningful biomarkers, even from a noisy signal sampled by a low-cost PPG sensor. The AUCs for best architectures put forward PPG wave as biological discriminant, reaching 79% and 89.0%, respectively for gender and person verification tasks. Furthermore, speech detection experiments reporting AUCs around 69% encourage us for further exploration about the feasibility of PPG for speech processing tasks.en
• dc.format.mimetype application/pdf
• dc.identifier.citation Cámbara G, Luque J, Farrús M. Detection of speech events and speaker characteristics through photo-plethysmographic signal neural processing. In: 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) Proceedings; 2020 May 4-8; Barcelona, Spain. New York: IEEE; 2020. p. 7564-8. DOI: 10.1109/ICASSP40776.2020.9052972
• dc.identifier.doi http://dx.doi.org/10.1109/ICASSP40776.2020.9052972
• dc.identifier.isbn 978-1-5090-6631-5
• dc.identifier.issn 1520-6149
• dc.identifier.uri http://hdl.handle.net/10230/44443
• dc.language.iso eng
• dc.publisher Institute of Electrical and Electronics Engineers (IEEE)
• dc.relation.ispartof 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) Proceedings; 2020 May 4-8; Barcelona, Spain. New York: IEEE; 2020. p. 7564-8.
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/RYC-2015-17239
• dc.rights © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. http://dx.doi.org/10.1109/ICASSP40776.2020.9052972
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Photoplethysmogram signalen
• dc.subject.keyword PPGen
• dc.subject.keyword Speech detectionen
• dc.subject.keyword Convolutional neural networksen
• dc.subject.keyword Biometric authenticationen
• dc.title Detection of speech events and speaker characteristics through photo-plethysmographic signal neural processingen
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion