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Noise annoyance and other effects of noise are reasonably correlated with A-weighted sound levels. Currently, the influence of low-frequency content and of sound emergence level (i.e. the sound level difference between total noise and residual noise) on effects of noise are being assessed in laboratories using stimuli based on recordings. Standards intended for regulations often include penalties depending on these factors. The difference between C-and A-weighted sound levels is frequently used as a descriptor of low frequency content. This work proposes a method to optimize the search and combination of a subset of audio files from a large set of noise sources recordings in order to achieve an environmental noise stimulus with previously specified values of factors (i) sound emergence level, (ii) C-A-weighted levels difference, (iii) A-weighted equivalent continuous sound level and (iv) duration of stimulus. The method is implemented, and one hundred stimuli are generated following a full factorial experimental design varying these four factors. The resulting stimuli show small differences between specified and measured values. The mean difference for factors i-iii is 0.46 dB and the maximum is 2.3 dB.

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Audio recordings are often used to improve ecological validity of stimuli for laboratory research on effects of noise. In this paper a method is proposed for composing realistic environmental sound stimuli with (1) specified overall spectrum and (2) specified statistical distribution of sound event durations and semantic categories. The combination is addressed as a mixed integer linear programming problem. Objective measurements, for eight stimuli and a moderate-size database, validate the method. The mean error in octave bands exposure level is 2.6 dB and the statistical distribution of sound event durations and semantic categories is perfectly matched.

No abstract