A method for environmental acoustic analysis improvement based on individual evaluation of common sources in urban areas

Noise levels of common sources such as vehicles, whistles, sirens, car horns and crowd sounds are mixed in urban soundscapes. Nowadays, environmental acoustic analysis is performed based on mixture signals recorded by monitoring systems. These mixed signals make it difficult for individual analysis which is useful in taking actions to reduce and control environmental noise. This paper aims at separating, individually, the noise source from recorded mixtures in order to evaluate the noise level of each estimated source. A method based on blind deconvolution and blind source separation in the wavelet domain is proposed. This approach provides a basis to improve results obtained in monitoring and analysis of common noise sources in urban areas. The method validation is through experiments based on knowledge of the predominant noise sources in urban soundscapes. Actual recordings of common noise sources are used to acquire mixture signals using a microphone array in semi-controlled environments. The developed method has demonstrated great performance improvements in identification, analysis and evaluation of common urban sources. •This work allows the identification and evaluation of estimated individual sources.•The method based on MBLMS and BSS achieves a successful separation of predominant noise sources.•The method was applied to recorded measurements in semi-controlled environments.•The evaluation results are based on recorded signals from a permanent monitoring system.•The use of estimated predominant sources allows identifying successfully masked sources in noisy areas.