Vehicle noise comfort level indication: A psychoacoustic approach

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Main Authors: Paulraj, Murugesa Pandiyan, Prof. Madya, Sazali, Yaacob, Prof. Dr., Andrew, Allan Melvin
Other Authors: paul@unimap.edu.my
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2010
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Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/10221
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spelling my.unimap-102212010-11-15T09:37:49Z Vehicle noise comfort level indication: A psychoacoustic approach Paulraj, Murugesa Pandiyan, Prof. Madya Sazali, Yaacob, Prof. Dr. Andrew, Allan Melvin paul@unimap.edu.my s.yaacob@unimap.edu.my allanmelvin.andrew@gmail.com Ride comfort Psychoacoustics Noise Vibration Neural network Link to publisher’s homepage at http://ieeexplore.ieee.org/ Nowadays, the studies and researches related to the improvement of the passenger comfort in the car are carried out vigorously. The comfort in the car interior is already become a need for the passengers and the buyers. Due to high competition in car industries, all the car manufacturers are concentrating in improving the interior noise comfort of the car. Vehicle Noise Comfort Index (VNCI) has been developed recently to evaluate the sound characteristics of passenger cars. VNCI indicates the interior vehicle noise comfort using a numeric scale from 1 to 10. Most of the researches are relating the vehicle interior sound quality to psychoacoustics sound metrics such as loudness and sharpness for the frequency between 20 Hz to 20 kHz. In this present paper, a vehicle comfort level indication is proposed to detect the comfort level in cars using artificial neural network. Determination of vehicle comfort is important because continuous exposure to the noise and vibration leads to health problems for the driver and passengers. The database of sound samples from 15 local cars is used. The sound samples are taken from two states, while the car is in stationary condition and while it is moving at a constant speed. Features such as the psychoacoustics criterions are extracted from the signals. The correlation between the subjective and the objective evaluation is also tested. The relationship between the VNCI and the sound metrics is modelled using a feed-forward neural network trained by back-propagation algorithm. 2010-11-15T09:37:49Z 2010-11-15T09:37:49Z 2010-05-21 Working Paper p.1-5 978-1-4244-7121-8 http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5545249 http://hdl.handle.net/123456789/10221 en Proceedings of the 6th International Colloquium on Signal Processing and Its Applications (CSPA) 2010 Institute of Electrical and Electronics Engineers (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Ride comfort
Psychoacoustics
Noise
Vibration
Neural network
spellingShingle Ride comfort
Psychoacoustics
Noise
Vibration
Neural network
Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
Andrew, Allan Melvin
Vehicle noise comfort level indication: A psychoacoustic approach
description Link to publisher’s homepage at http://ieeexplore.ieee.org/
author2 paul@unimap.edu.my
author_facet paul@unimap.edu.my
Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
Andrew, Allan Melvin
format Working Paper
author Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
Andrew, Allan Melvin
author_sort Paulraj, Murugesa Pandiyan, Prof. Madya
title Vehicle noise comfort level indication: A psychoacoustic approach
title_short Vehicle noise comfort level indication: A psychoacoustic approach
title_full Vehicle noise comfort level indication: A psychoacoustic approach
title_fullStr Vehicle noise comfort level indication: A psychoacoustic approach
title_full_unstemmed Vehicle noise comfort level indication: A psychoacoustic approach
title_sort vehicle noise comfort level indication: a psychoacoustic approach
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2010
url http://dspace.unimap.edu.my/xmlui/handle/123456789/10221
_version_ 1643789789717069824
score 13.209306