Monitoring of human and social activities is becoming increasingly pervasive in our living
environment for public security and safety applications. The recognition of suspicious events …

Acoustic scene classification (ASC) has gained significant interest recently due to its diverse
applications. Various audio signal processing and machine learning methods have been …

In this paper, we propose a parallel Convolutional Neural Network architecture for the task of
classifying acoustic scenes and urban sound scapes. A popular choice for input to a …

Surveillance systems based on image analysis can automatically detect road accidents to
ensure a quick intervention by rescue teams. However, in some situations, the visual …

Acoustic event detection in surveillance scenarios is an important but difficult problem.
Realistic systems are struggling with noisy recording conditions. In this work, we propose to …

To test if simultaneous spectral and temporal processing is required to extract robust
features for automatic speech recognition (ASR), the robust spectro-temporal two …

The analysis of sound information is helpful for audio surveillance, multimedia information
retrieval, audio tagging, and forensic applications. Environmental audio scene recognition …

A framework for simulating auditory discrimination experiments, based on an approach from
Schädler, Warzybok, Hochmuth, and Kollmeier [(2015). Int. J. Audiol. 54, 100–107] which …

Algorithms for the automatic detection and recognition of acoustic events are increasingly
gaining relevance for the reliable and robust functioning of consumer, assistive and …

This chapter explains the basic concepts in computational methods used for analysis of
sound scenes and events. Even though the analysis tasks in many applications seem …