Audio recognition can be used in smart cities for security, surveillance, manufacturing,
autonomous vehicles, and noise mitigation, just to name a few. However, urban sounds are …

A person's behavior significantly influences their health and well-being. It also contributes to
the social environment in which humans interact, with cascading impacts to the health and …

Automatically recognizing activities of heavy construction equipment using sound data has
recently received considerable attention as a promising research area in construction …

Audio segmentation and sound event detection are crucial topics in machine listening that
aim to detect acoustic classes and their respective boundaries. It is useful for audio-content …

This paper presents a new approach based on recurrent neural networks (RNN) to the
multiclass audio segmentation task whose goal is to classify an audio signal as speech …

The cocktail party problem aims at isolating any source of interest within a complex acoustic
scene, and has long inspired audio source separation research. Recent efforts have mainly …

One of the principal tasks of machine learning with major applications is text classification.
This paper focuses on the legal domain and, in particular, on the classification of lengthy …

A bioacoustical animal recognition system is composed of two parts:(1) the segmenter,
responsible for detecting syllables (animal vocalization) in the audio; and (2) the classifier …

We propose a new method for music detection from broadcasting contents using the
convolutional neural networks with a Mel-scale kernel. In this detection task, music …

Automatic speech and music activity detection (SMAD) is an enabling task that can help
segment, index, and pre-process audio content in radio broadcast and TV programs …