Development of a Sound Quality Evaluation Model Based on an Optimal Analytic Wavelet Transform and an Artificial Neural Network

• Autorzy: Pourseiedrezaei Mehdi , Loghmani Ali , Keshmiri Mehdi

Identyfikatory

DOI

10.24425/aoa.2021.136560

• Języki publikacji: EN

Abstrakty

EN

The purpose of this study was to develop a sound quality model for real time active sound quality control systems. The model is based on an optimal analytic wavelet transform (OAWT) used along with a back propagation neural network (BPNN) in which the initial weights and thresholds are determined by particle swarm optimisation (PSO). In the model the input signal is decomposed into 24 critical bands to extract a feature matrix, based on energy, mean, and standard deviation indices of the sub signal scalogram obtained by OAWT. The feature matrix is fed into the neural network input to determine the psychoacoustic parameters used for sound quality evaluation. The results of the study show that the present model is in good agreement with psychoacoustic models of sound quality metrics and enables evaluation of the quality of sound at a lower computational cost than the existing models.

Słowa kluczowe

EN

analytic wavelet transform; AWT; sound quality evaluation; SQE; psychoacoustic metrics; back propagation neural network; BPNN

• Wydawca: Instytut Podstawowych Problemów Techniki PAN ; Komitet Akustyki PAN ; Polskie Towarzystwo Akustyczne
• Czasopismo: Archives of Acoustics
• Rocznik: 2021
• Tom: Vol. 46, No. 1
• Strony: 55--65
• Opis fizyczny: Bibliogr. 35 poz., rys., tab., wykr.

Twórcy

autor

Pourseiedrezaei Mehdi

• Mechanical Engineering Group, Pardis College, Isfahan University of Technology, Isfahan 84156-83111, Iran

autor

Loghmani Ali

• Department of Mechanical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran

autor

Keshmiri Mehdi

• Department of Mechanical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).