The purpose of this paper is to study noticeability of sounds as a function of sound level and sound character. Noticing an event should be a prerequisite for annoyance; one should need to notice an event for it to be annoying and for it to contribute to an overall impression of annoyance. This noticeability should be a function of the character of the sound. For example, for the same A-weighted sound exposure, a helicopter may be much more noticeable than a fixed-wing aircraft because of the impulsive blade-slap sound. This study was performed in situ, in respondents' homes; there were no artificial sounds or tape recordings. Clusters of subjects were chosen and an outdoor sound monitor was used to measure single-event A-weighted sound exposure level (ASEL) and record the times at which they occurred. The three sources studied were helicopters, fixed-wing aircraft, and trains. For the same ASEL, helicopter sounds were not found to generate any greater annoyance per event than did the other two sounds. Rate of response was used as the main indicator of noticeability. The rate of response function for helicopter sounds grew at 3 times the rate of response functions found for airplanes at Los Angeles airport and trains at Aberdeen Proving Ground. Thus, this paper shows that sound noticeability may be a significant variable for predicting human response to noise. The character of the sound is a key ingredient to noticeability. Helicopters, with their distinct sound character, appear to be more noticeable than other sounds for the same A-weighted sound exposure level.
On the contribution of noticeability of environmental sounds to noise annoyance
Untersuchungen zum wahrnehmbaren Anteil von Umweltgeräuschen an Lärmbelästigungseffekten
Noise Control Engineering Journal ; 44 , 6 ; 294-305
1996
12 Seiten, 10 Bilder, 4 Tabellen, 9 Quellen
Article (Journal)
English
Editorial - Noticeability and Audibility
Online Contents | 1999
Noticeability of a decrease in aircraft noise
Tema Archive | 1998
|Traffic noise: Annoyance assessment of real and virtual sounds based on close proximity measurements
BASE | 2017
|