@article {Fu:2017:0736-2935:5997,
title = "Spectral Modelling Synthesis of Vehicle Pass-by Noise",
journal = "INTER-NOISE and NOISE-CON Congress and Conference Proceedings",
parent_itemid = "infobike://ince/incecp",
publishercode ="ince",
year = "2017",
volume = "255",
number = "1",
publication date ="2017-12-07T00:00:00",
pages = "5997-6006",
itemtype = "ARTICLE",
issn = "0736-2935",
url = "https://ince.publisher.ingentaconnect.com/content/ince/incecp/2017/00000255/00000001/art00001",
author = "Fu, Yang and Murphy, Damian",
abstract = "Spectral Modelling Synthesis (SMS) is a sound synthesis technique that models time-varying spectra of given sounds as a collection of sinusoids plus filtered noise component. Although originally utilized to produce musical sounds, this technique can also be extended for analysis, transformation
and synthesis of a wider range of environmental sounds, such as vehicle noise. Simplifications based on psychoacoustics are conducted during the modelling process to extract only useful information so as to avoid redundant data, which leads to perceptually similarity between the synthesized
and the original sounds. In this paper, we investigated if the perceptually similarity can be described using an objective sound quality metric, and how to improve the sound quality of the synthesized vehicle pass-by noise by tuning the parameters in the algorithm. The results showed that
vehicle pass-by sounds dominant by tire and engine noise should be treated separately with different parameter sets for SMS. Furthermore, Zwicker roughness and sharpness can be used as a metric when tuning parameters, as these descriptors are relatively sensitive to the variation of parameter
sets for SMS.",
}