Xing, C; Yu, L; Kang, J; Tao, Z; (2019) Evaluating shenzhen sound environment by using artificial neural networks. In: Proceedings of the 23rd International Congress on Acoustics: integrating 4th EAA Euroregio 2019: 9-13 September 2019 in Aachen, Germany. (pp. pp. 821-828). International Congress on Acoustics: Berlin, Germany.

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Abstract

Attenuating absolute sound level for urban noise control is not always efficient in which sound meanings has to be included. As evolving from fish-villages with a coastal rural topography, Shenzhen possesses a diversity sound environment containing various ecological sounds. In order to get right knowledge for controlling Shenzhen sound environments, sound meanings have to be measured to give a complete profile. Through a series field studies in Shenzhen, 702 samples covering various sound environments were got. Statistical analyses of heterogeneity of sound environments in Shenzhen were firstly examined. Based on results of subject evaluation of sound level present in a former study, Shenzhen sound environment referring sound levels were investigated. Furthermore, annoyance evaluations to various sounds with a same level 65dB were made using field study data. In order to measure sound meaning attributes influencing sound environment quality, plenty ANN models were developed to predict annoyance evaluations according to sound meaning differences. Finally, combining the results of sound levels and sound meaning, predicting models to a sound environment in Shenzhen were given to provide a feasible tool in measuring and solving Shenzhen noise problems.

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