Using Smartphones to Classify Urban Sounds

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Gomes, EF (Author) Other; Batista, F (Author) Other; Jorge, AM (Author) FCUP

Conference proceedings International

Title: ACM International Conference Proceeding Series

Pages: 67-72

9th International C* Conference on Computer Science and Software Engineering, C3S2E 2016

20 July 2016 through 22 July 2016

Indexing

Scopus - 3 Citations

Other information

Authenticus ID: P-00K-S95

DOI: 10.1145/2948992.2949002

Abstract (EN): 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. Copyright 2016 ACM.

Language: English

Type (Professor's evaluation): Scientific