Automatic environmental sound classification (ESC) is one of the upcoming areas of
research as most of the traditional studies are focused on speech and music signals …

The concept of Acoustic Source Identification (ASI), which refers to the process of identifying
noise sources has attracted increasing attention in recent years. The ASI technology can be …

Convolutional neural networks (CNNs) with log-mel audio representation and CNN-based
end-to-end learning have both been used for environmental event sound recognition (ESC) …

Environmental sounds are unstructured and similar to noise. However, the recognition of
environmental sounds can benefit crime investigations, warning systems for elderly persons …

This paper presents the real-time implementation and field testing of an app running on
smartphones for classifying noise signals involving subband features and a random forest …

We investigate the suitability of semi-supervised learning in sound event classification on a
large database of 17 k sound clips. Seven categories are chosen based on the findsounds …

One of the main priorities of smart cities is improving the quality of life of their inhabitants.
Traffic noise is one of the pollutant sources that causes a negative impact on the quality of …

Several biological research studies have shown that the number of individuals of certain
species of anurans in a specific geographical region, and the evolution of this number over …

Temporal feature integration refers to a set of strategies attempting to capture the information
conveyed in the temporal evolution of the signal. It has been extensively applied in the …

Sound events can be used to establish context to assist a user to perform context-dependent
tasks. The state of the art methods allow the identification of isolated sound events, even …