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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.)

Wavelet-packets Associated with Support Vector Machine Are Effective for Monophone Sorting in Music Signals

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Author(s):
Scalvenzi, Rafael Rubiati [1] ; Guido, Rodrigo Capobianco [1] ; Marranghello, Norian [1]
Total Authors: 3
Affiliation:
[1] Sao Paulo State Univ, Univ Estadual Paulista, UNESP, Inst Biociencias Letras & Ciencias Exatas, Rua Cristovao Colombo 2265, BR-15054000 Sao Jose Do Rio Preto, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING; v. 13, n. 3, p. 415-425, SEP 2019.
Web of Science Citations: 0
Abstract

An abstract interpretation is usually required to analyze acoustic compositions. Nevertheless, there is much signal processing-related research focusing on music processing and similar topics. In that context, the semantic information contained in the melody involving major and minor chords, sharps and flats associated with semibreve, minim, crotchet, quaver, semiquaver and demisemiquaver notes can help in the study of musical sounds. Thus, multiresolution analysis based on discrete wavelet-packet transform (DWPT) associated with a support vector machine (SVM) is used in this paper to inspect and classify those signals, correlating them with a respective acoustic pattern. Results over hundreds of inputs provided almost full accuracy, reassuring the efficacy of the proposed approach for both off-line and real-time usage. (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