TY - JOUR
T1 - Use of autocorrelation analysis to characterize audibility of low-frequency tonal signals
AU - Ryu, Jongkwan
AU - Sato, Hiroshi
AU - Kurakata, Kenji
N1 - Funding Information:
This work was partially supported by a grant for Environmental Research from the Japanese Ministry of Environment in Japan . The first author's work was also supported by the Postdoctoral Fellowship Program for Foreign Researchers from the Japan Society for the Promotion of Science. The authors thank Yukio Inukai for his valuable comments.
Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011/10/10
Y1 - 2011/10/10
N2 - Autocorrelation function (ACF) parameters were used to identify low-frequency tonal sound detected in actual living environments. Five houses whose residents had made complaints for unidentified noise were selected as measurement sites. The sounds and the residents detection responses were recorded simultaneously inside a room in each house. When they heard the suspected noise, the participants pushed a response button on a portable recording device as the sound was recorded. Results showed that tonal components in the low-frequency range were highly correlated with the sound detection. This study suggests that autocorrelation analysis can reveal the human detection of low-frequency tonal signals. Low-frequency tonal components were identified and quantified using ACF parameters: the delay time and amplitude of the ACFs first dominant peak. The amplitude was useful to describe the detection and prominence of low-frequency tonal components in noise.
AB - Autocorrelation function (ACF) parameters were used to identify low-frequency tonal sound detected in actual living environments. Five houses whose residents had made complaints for unidentified noise were selected as measurement sites. The sounds and the residents detection responses were recorded simultaneously inside a room in each house. When they heard the suspected noise, the participants pushed a response button on a portable recording device as the sound was recorded. Results showed that tonal components in the low-frequency range were highly correlated with the sound detection. This study suggests that autocorrelation analysis can reveal the human detection of low-frequency tonal signals. Low-frequency tonal components were identified and quantified using ACF parameters: the delay time and amplitude of the ACFs first dominant peak. The amplitude was useful to describe the detection and prominence of low-frequency tonal components in noise.
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U2 - 10.1016/j.jsv.2011.04.037
DO - 10.1016/j.jsv.2011.04.037
M3 - Article
AN - SCOPUS:79960556377
VL - 330
SP - 5210
EP - 5222
JO - Journal of Sound and Vibration
JF - Journal of Sound and Vibration
SN - 0022-460X
IS - 21
ER -