Application of the SVM algorithm for the development of a model classification of the visual and sound landscape

Abstract

To ensure adequate management of the soundscape in urban environments, urban planning authorities need a range of tools that enable them to perform this condition. Analyzing and classifying a soundscape is necessary to adapt it to the expectations of the people who inhabit it. The term Soundscape is associated with three different research areas: ecology / anthropology, music / sound design and architecture / urbanism. In particular, in this paper, the third research area will be investigated, finding a correlation model between auditory and visual sensations of the urban landscape of the port of Ancona. The classification model that is used is the Support Vector Machines SVM which is proposed as a tool for a global assessment of the urban sound landscape. In this case study the algorithm is intended for the automatic classification of the sound landscape of the port of Ancona to understand how much the sound perception affects the visual one. The main results obtained are illustrated: - 75 participants were selected who, after spending time in the indicated place, filled out a questionnaire consisting of 20 questions for the evaluation of the visual environment and 20 questions for the evaluation of the sound environment. - The training set (train \ _data) will consist of 1500 samples for images and 1500 samples for sounds. - By applying the fitcsvm (SMO) algorithm, the value of each parameter used for the implementation algorithm was obtained and a random partition of the data was performed for a k-Fold cross-validation. -Finally, the hyperplane equation of our specific system was calculated.