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

Pourseiedrezaei Mehdi, Loghmani Ali, Keshmiri Mehdi

Archives of Acoustics

2021

Vol. 46, No. 1

55--65

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.

Modelling for sound annoyance evaluation of vehicle noise based on neural network

Wang Y., Shen G., Guo H.

Przegląd Elektrotechniczny

2012

R. 88, nr 7b

303--306

Based on the neural network (NN) technique, a new sound quality evaluation (SQE) model for synthetical annoyance of vehicle noises is proposed in this paper. Based on the measured noise signals of a sample vehicle, the psychoacoustical models for loudness, sharpness and roughness are investigated. Annoyance values of the measured vehicle noises are estimated by a jury test following an anchor-scaled scoring method. A NN-based model for annoyance evaluation of vehicle noise, so-called VNA-NNM, is carried out. Finally, the VNA-NNM model is verified by the leave-one-out algorithm. The results suggest that the VNA-NNM model is accurate and effective for estimating sound quality of vehicle interior noises, which is instructive and useful for vehicle acoustical designs.

Zaproponowano model oceny jakości dźwięku i rozdrażnienia dźwiękiem szumu samochodowego. Model bazuje na sieciach neuronowych i wykorzystuje zmierzony sygnał szumu samochodowego oraz model psychoakustyczny.