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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Introducing the Discrete Path Transform (DPT) and its applications in signal analysis, artefact removal, and spoken word recognition

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Author(s):
Guido, Rodrigo Capobianco [1] ; Pedroso, Fernando [2, 1] ; Contreras, Rodrigo Colnago [1, 3] ; Rodrigues, Luciene Cavalcanti [1, 4, 5] ; Guariglia, Emanuel [1, 6] ; Neto, Jogi Suda [1]
Total Authors: 6
Affiliation:
[1] Sao Paulo State Univ, Inst Biociencias Letras & Ciencias Exatas, Unesp Univ Estadual Paulista, Rua Cristovao Colombo 2265, BR-15054000 Sao Jose Do Rio Preto, SP - Brazil
[2] Ctr Estadual Educ Tecnol Paula Souza CEETEPS, Sao Paulo, SP - Brazil
[3] Univ Sao Paulo ICMC USP, Inst Ciencias Matemat & Computacao, Av Trabalhador SaoCarlense 400, BR-13560970 Sao Carlos, SP - Brazil
[4] Inst Fed Educ Ciencia & Tecnol Sao Paulo, Ave Jeronimo Figueira Costa 3014, Votuporanga, SP - Brazil
[5] Fac Tecnol Sao Jose Do Rio Preto, Rua Fernandopolis 2510, Sao Jose Do Rio Preto, SP - Brazil
[6] Univ Bologna, Dept Biol Geol & Environm Sci BIGeA, Via Zamboni 33, I-40126 Bologna - Italy
Total Affiliations: 6
Document type: Journal article
Source: DIGITAL SIGNAL PROCESSING; v. 117, OCT 2021.
Web of Science Citations: 1
Abstract

This article introduces the Discrete Path Transform (DPT). Designed to serve as a new tool for handcraft feature extraction (FE), it improves the elementary analysis provided by signal energy (E) and enhances the humble spectral investigation granted by zero-crossing rates (ZCRs). C/C++ source-codes to realize both the DPT direct and inverse (IDPT) forms are presented together with a few hypothetical numerical examples and an application involving general signal analysis, artefact removal from biomedical signals, and spoken word recognition (SWR), thus demonstrating how useful and effective the proposed transform is. Brief comparisons with Teager Energy Operator (TEO) and a list of important references were also included. (C) 2021 Elsevier Inc. All rights reserved. (AU)

FAPESP's process: 19/04475-0 - Paraconsistent Feature Analysis of Speech Signals: fighting the voice spoofing attacks
Grantee:Rodrigo Capobianco Guido
Support Opportunities: Regular Research Grants