@inproceedings{77b6f81ca1a84b82a8d2977c0eb1d7ae,
title = "Acoustic scenery recognition using CWT and deep neural network",
abstract = "The development of acoustic scenes recognition systems has been a topic of extensive research due to its applications in several fields of science and engineering. This paper proposes an environmental system in which firstly a time-frequency representation is obtained using the Continuous Wavelet Transform (CWT). The time frequency representation is then represented as a color image using the Viridis color map, which is then inserted into a Deep Neural Network (DNN) to carry out the classification task. Evaluation results using several public data bases show that proposed scheme provides a classification performance better than the performance provided by other previously proposed schemes.",
keywords = "Acoustic scenes recognition, Automatic sound recognition, continuous wavelet transform, deep neural network, deep neural networks",
author = "Francisco Mondragon and Jonathan Jimenez and Mariko Nakano and Toru Nakashika and Hector Perez-Meana",
note = "Publisher Copyright: {\textcopyright} 2021 The authors and IOS Press. All rights reserved.; 20th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2021 ; Conference date: 21-09-2021 Through 23-09-2021",
year = "2021",
month = sep,
day = "8",
doi = "10.3233/FAIA210029",
language = "Ingl{\'e}s",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "303--312",
editor = "Hamido Fujita and Hector Perez-Meana",
booktitle = "New Trends in Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 20th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2021",
}