Sound quality metrics applied to road noise evaluation

2018 ◽  
Vol 144 (3) ◽  
pp. 1930-1931
Author(s):  
Karolina Marciniuk ◽  
Bozena Kostek
Keyword(s):  
Sound Quality ◽  
Quality Metrics ◽  
Road Noise ◽  
Noise Evaluation

Perception of stationary wind noise in vehicles

2021 ◽  
Vol 69 (1) ◽  
pp. 53-65
Author(s):  
Daniel Carr ◽  
Patricia Davies
Keyword(s):  
Wind Tunnel ◽  
Sound Quality ◽  
Quality Metrics ◽  
Aerodynamic Noise ◽  
Road Noise ◽  
Wind Noise ◽  
Listening Studies ◽  
Signal Modification ◽  
Made In

Predictors of people's responses to noise inside cars are used by car companies to identify and address potential noise problems from tests. Because significant improvements have been made in engine, powertrain, and tire/road noise, it is now important to pursue improvements in wind or aerodynamic noise. While models of loudness are commonly used to predict people's responses to stationary wind noise, some wind noises are less acceptable than is predicted by loudness metrics. Additional sound characteristics may account for this. Three listening studies were designed to examine the usefulness of including additional sound quality metrics with loudness in models used to predict acceptability for stationary wind-noise sounds. Test sounds were based on recordings made in cars in a wind tunnel. Signal modification techniques were developed to decorrelate metrics across a set of sounds and to examine how acceptability changes with strengths of particular sound characteristics. Models of acceptability for stationary wind noise are significantly improved when a metric that predicts the sharpness of a sound is included in the model with the loudness metric.

Road Noise Evaluation by Sound Quality Simulation Module

2020 ◽  
Author(s):  
Perry Gu ◽  
Jie Mao ◽  
Zhidong Chen ◽  
Zhi Ding ◽  
Lei Cheng ◽  
...  
Keyword(s):  
Sound Quality ◽  
Road Noise ◽  
Noise Evaluation

Use of Psychoacoustic Metrics for the Analysis of Next Generation Computer Graphic Card Noise

2005 ◽  
Author(s):  
Colin Novak ◽  
Helen Ule ◽  
Robert Gaspar ◽  
Gamal Refai-Ahmed
Keyword(s):  
Computer Graphic ◽  
Sound Quality ◽  
Quality Metrics ◽  
Passive Cooling ◽  
Air Cooling ◽  
Analysis Tool ◽  
Processing Unit ◽  
Fan Noise ◽  
Analysis Techniques ◽  
Psychoacoustic Metrics

The continuing challenge to deliver performance improvements in computer graphic cards has long since progressed to the point of requiring finned, passive, cooling devices to dissipate the heat generated by the graphics processing unit (GPU). The heat flux generated by further improvements now exceeds that dissipation capacity so that passive cooling can no longer provide adequate cooling the GPU. The dissipation rates required by the latest generation of designs can be delivered by forced air cooling of finned heat sinks. The concurrent challenge to the industry is to provide this cooling while minimizing the noise generated by these cooling fans. A significant aspect associate with this problem is missed if one only considers the problem to be a one-dimensional sound level issue. From a consumer’s perspective, the perceived quality of the noise emitted takes precedence over what traditional acoustical analysis techniques of this fan noise may imply. Here, psychoacoustic or sound quality metrics, may be a more applicable analysis tool as it provides the quantification of these qualitative human impressions. The present study investigates the validity of using several psychoacoustic metrics for the analysis of fan cooled computer graphics card noise. Using experimentally measured fan noise from three different cooling fan designs, a sound quality analysis was performed using loudness, sharpness, roughness, fluctuation strength, prominent tone and articulation index. A discussion and comparison of measured results using traditional analysis techniques is also included. It was found that some of the metrics proved more useful than others as an analysis tool for this specific noise source. A discussion of the applicability of the various sound quality metrics along with justifications is presented.

MOSQITO: an open-source and free toolbox for sound quality metrics in the industry and education

2021 ◽  
Vol 263 (5) ◽  
pp. 1164-1175
Author(s):  
Roberto San Millán-Castillo ◽  
Eduardo Latorre-Iglesias ◽  
Martin Glesser ◽  
Salomé Wanty ◽  
Daniel Jiménez-Caminero ◽  
...  
Keyword(s):  
Open Source ◽  
Programming Languages ◽  
Open Source Software ◽  
Objective Assessment ◽  
Sound Quality ◽  
Quality Metrics ◽  
Point Of View ◽  
Wide Range ◽  
Efficient Learning ◽  
High Level

Sound quality metrics provide an objective assessment of the psychoacoustics of sounds. A wide range of metrics has been already standardised while others remain as active research topics. Calculation algorithms are available in commercial equipment or Matlab scripts. However, they may not present available data on general documentation and validation procedures. Moreover, the use of these tools might be unaffordable for some students and independent researchers. In recent years, the scientific and technical community has been developing uncountable open-source software projects in several knowledge fields. The permission to use, study, modify, improve and distribute open-source software make it extremely valuable. It encourages collaboration and sharing, and thus transparency and continuous improvement of the coding. Modular Sound Quality Integrated Toolbox (MOSQITO) project relies on one of the most popular high-level and free programming languages: Python. The main objective of MOSQITO is to provide a unified and modular framework of key sound quality and psychoacoustics metrics, free and open-source, which supports reproducible testing. Moreover, open-source projects can be efficient learning tools at University degrees. This paper presents the current structure of the toolbox from a technical point of view. Besides, it discusses open-source development contributions to graduates training.

Certification of vehicles used for tire/road noise evaluation by CPX method

2009 ◽  
Vol 57 (2) ◽  
pp. 121 ◽  
Author(s):  
Jerzy A. Ejsmont ◽  
Piotr Mioduszewski
Keyword(s):  
Road Noise ◽  
Noise Evaluation
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