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 …

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

Since the advent of personal computing devices, intelligent personal assistants (IPAs) have
been one of the key technologies that researchers and engineers have focused on, aiming …

With the development of multi-modal man-machine interaction, audio signal analysis is
gaining importance in a field traditionally dominated by video. In particular, anomalous …

One of the most amazing functions of the human auditory system is the ability to detect all
kinds of sound events in the environment. With the technologies and hardware advances …

The operation state of machine can be monitored by performing anomalous sound detection
(ASD). Unsupervised-ASD is a detection task in which the model detects unknown …

In the last decade, Anomalous Sound Detection (ASD) is becoming an increasingly
challenging task for a plethora of applications due to the widespread diffusion of Deep …

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 …

One dimension convolutional neural networks (1D CNN) that directly take raw waveforms as
input has less competition than 2D CNN recognizing environmental sound. In order to …

Abstract Acoustic Scene Classification (ASC) is the task of assigning a semantic label to an
audio recording, based on the surrounding environment. In this work, a Fisher network is …