In acoustic event detection, the training data size of some acoustic events is often small and
imbalanced. To deal with this, this paper proposes generating the virtual training data …

The variety of event categories and event boundary information have resulted in limited
success for acoustic event detection systems. To deal with this, we propose to utilize the …

Acoustic event detection deals with the acoustic signals to determine the sound type and to
estimate the audio event boundaries. Multi-label classification based approaches are …

In the age of smart cities, it is envisioned that most processes within the smart city context
will be smart and automated. This includes smart houses, smart kitchens, etc. within this …

Acoustic event detection, the determination of the acoustic event type and the localisation of
the event, has been widely applied in many real-world applications. Many works adopt multi …

Sound event detection (SED) has been widely applied in real world applications.
Convolutional recurrent neural network based SED approaches have achieved state-of-the …

This paper presents an approach for acoustic scene classification using the local binary
pattern (LBP) and random forest (RF). The audio signal is converted to a Constant-Q …

The classification framework has been popularly adopted to perform sound event detection.
However, the existing neural network based classification based approaches treat each …

In this paper, we propose a class wise distance based approach in a neural network based
acoustic event detection system. The neural network output probabilities are updated by …

With the growth in the complexity of real-time embedded systems, there is an increasing
need for tools and techniques to understand and compare the observed runtime behavior of …