Models of natural background noise and masking of wind turbine noise

2008 ◽  
Vol 123 (5) ◽  
pp. 3535-3535
Author(s):  
Karl Bolin
Keyword(s):  
Wind Turbine ◽  
Background Noise ◽  
Natural Background ◽  
Wind Turbine Noise ◽  
Natural Background Noise

scholarly journals Effect of Natural Background Noise and Man-Made Noise on Automated Frog Calls Identification System

2021 ◽  
Vol 3 (1) ◽  
pp. 208-213
Author(s):  
Haryati Jaafar ◽  
Dzati Athiar Ramli
Keyword(s):  
Background Noise ◽  
Experimental Studies ◽  
Outdoor Environment ◽  
Biological Research ◽  
Identification System ◽  
Natural Background ◽  
K Nearest Neighbor ◽  
Zero Crossing ◽  
Short Time ◽  
Natural Background Noise

Frog identification based on their calls becomes important for biological research and environmental monitoring. However, identifying particular frog calls becomes challenging particularly when the frog calls are interrupted with noises either in natural background noise or man-made noise. Hence, an automatic identification frog call system that robust in noisy environment has been proposed in this paper. Experimental studies of 675 audio obtained from 15 species of frogs in the Malaysian forest and recorded in an outdoor environment are used in this study. These audio data are then corrupted by 10dB and 5dB noise. A syllable segmentation technique i.e. short time energy (STE) and Short Time Average Zero Crossing Rate (STAZCR) and feature extraction, Mel-Frequency Cepstrum Coefficients (MFCC) are employed to segment the desired syllables and extract the segmented signal. Subsequently, the Local Mean k-Nearest Neighbor with Fuzzy Distance Weighting (LMkNN-FDW) are employed as a classifier in order to evaluate the performance of the identification system. The experimental results show both of natural background noise and man-made noise outperform by 95.2% and 88.27% in clean SNR, respectively.

scholarly journals Speech Recognition in Natural Background Noise

PLoS ONE ◽  
2013 ◽  
Vol 8 (11) ◽  
pp. e79279 ◽  
Author(s):  
Julien Meyer ◽  
Laure Dentel ◽  
Fanny Meunier
Keyword(s):  
Speech Recognition ◽  
Background Noise ◽  
Natural Background ◽  
Natural Background Noise

The effect of wind turbine noise on polysomnographically-measured and self-reported sleep latency in wind turbine noise naïve participants

SLEEP ◽  
2021 ◽  
Author(s):  
Tessa Liebich ◽  
Leon Lack ◽  
Gorica Micic ◽  
Kristy Hansen ◽  
Branko Zajamsek ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Background Noise ◽  
Mixed Model ◽  
Noise Exposure ◽  
Linear Mixed Model ◽  
Sleep Latency ◽  
Sleep Onset ◽  
Sleep Diary ◽  
Wind Turbine Noise ◽  
The Impact

Abstract Study Objectives Wind turbine noise exposure could potentially interfere with the initiation of sleep. However, effects on objectively assessed sleep latency are largely unknown. This study sought to assess the impact of wind turbine noise on polysomnographically-measured and sleep diary-determined sleep latency compared to control background noise alone in healthy good sleepers without habitual prior wind turbine noise exposure. Methods Twenty-three wind turbine noise naïve urban residents (mean±standard deviation age: 21.7±2.1 years, range 18-29, 13 females) attended the sleep laboratory for two polysomnography studies, one week apart. Participants were blind to noise conditions and only informed that they may or may not hear noise during each night. During the sleep onset period, participants were exposed to counterbalanced nights of wind turbine noise at 33 dB(A), the upper end of expected indoor values; or background noise alone as the control condition (23 dB(A)). Results Linear mixed model analysis revealed no differences in log10 normalized objective or subjective sleep latency between the wind turbine noise versus control nights (median [interquartile range] objective 16.5 [11.0 to 18.5] versus 16.5 [10.5 to 29.0] minutes, p = 0.401; subjective 20.0 [15.0 to 25.0] versus 15.0 [10.0 to 30.0] minutes, p = 0.907). Conclusions Although undetected small effects cannot be ruled out, these results do not support that wind turbine noise extends sleep latency in young urban dwelling individuals without prior wind turbine noise exposure.

Tonality evaluation of wind turbine noise by filter-segmentation

Measurement ◽  
2012 ◽  
Vol 45 (4) ◽  
pp. 711-718 ◽  
Author(s):  
Xiaofeng Liu ◽  
Lin Bo ◽  
Martin Veidt
Keyword(s):  
Wind Turbine ◽  
Wind Turbine Noise
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