Using Smartphones to Classify Urban Sounds | Zendy

Elsa Ferreira Gomes | Zendy; Fábio Miguel Moreira Batista | Zendy; Alí­pio Jorge | Zendy

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Using Smartphones to Classify Urban Sounds

Author(s) -

Elsa Ferreira Gomes,

Fábio Miguel Moreira Batista,

Alípio Jorge

Publication year - 2016

Publication title -

portuguese national funding agency for science, research and technology (rcaap project by fct)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1145/2948992.2949002

Subject(s) - mel frequency cepstrum , computer science , classifier (uml) , random forest , support vector machine , android (operating system) , artificial intelligence , machine learning , speech recognition , pattern recognition (psychology) , feature extraction , data mining , operating system

The aim of this work is to develop an application for Android able to classifying urban sounds in a real life context. It also enables the collection and classification of new sounds. To train our classifier we use the UrbanSound8K data set available online. We have used a hybrid approach to obtain features, by combining SAX-based multiresolution motif discovery with Mel-Frequency Cepstral Coefficients (MFCC). We also describe different configurations of motif discovery for defining attributes and compare the use of Random Forest and SVM algorithms on this kind of data.

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