A tool for urban soundscape evaluation applying Support Vector Machines for developing a soundscape classification model

Torija Martinez, AJ ORCID: https://orcid.org/0000-0002-5915-3736, Ruiz, DP and Ramos-Ridao, A 2014, 'A tool for urban soundscape evaluation applying Support Vector Machines for developing a soundscape classification model' , Science of the Total Environment, 482-83 , pp. 440-451.

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To ensure appropriate soundscape management in urban environments, the urban-planning authorities need a range of tools that enable such a task to be performed. An essential step during the management of urban areas from a sound standpoint should be the evaluation of the soundscape in such an area. In this sense, it has beenwidely acknowledged that a subjective and acoustical categorization of a soundscape is the first step to evaluate it, providing a basis for designing or adapting it to match people's expectations as well. In this sense, this work proposes a model for automatic classification of urban soundscapes. This model is intended for the automatic classification of urban soundscapes based on underlying acoustical and perceptual criteria. Thus, this classificationmodel is proposed to be used as a tool for a comprehensive urban soundscape evaluation. Because of the great complexity associated with the problem, two machine learning techniques, Support Vector Machines (SVM) and Support Vector Machines trained with Sequential Minimal Optimization (SMO), are implemented in developing model classification. The results indicate that the SMO model outperforms the SVM model in the specific task of soundscape classification. With the implementation of the SMO algorithm, the classification model achieves an outstanding performance (91.3% of instances correctly classified).

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Science of the Total Environment
Publisher: Elsevier
ISSN: 0048-9697
Related URLs:
Funders: University of Malaga and the European Commission, seventh Framework Programme for R&D of the EU, granted within the People Programme, “Co-funding of Regional, National and International Programmes” (COFUND), “Ministerio de Economía y Competitividad” of Spain
Depositing User: Dr Antonio J Torija Martinez
Date Deposited: 03 Dec 2019 15:12
Last Modified: 16 Feb 2022 03:28
URI: https://usir.salford.ac.uk/id/eprint/53219

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