In this work, a new grid-free global optimization algorithm that combined the image source
model (ISM) and state transition algorithm (STA) was proposed to realize the sound source …

Existing datasets for audio understanding primarily focus on single-turn interactions (ie
audio captioning, audio question answering) for describing audio in natural language, thus …

In our day-to-day life, observation of human and social actions are highly important for public
protection and security. Additionally, identifying suspicious activity is also essential in critical …

In recent years, deep learning techniques have been well explored to accomplish sound
classification tasks and in particular, in the classification of environmental sounds. Despite …

Audio signal processing is the most challenging field in the current era for an analysis of an
audio signal. Audio signal classification (ASC) comprises of generating appropriate features …

Real-world sound signals exhibit various aspects of grouping and profiling behaviors, such
as being recorded from identical sources, having similar environmental settings, or …

In this work Gammatone (GT) filter bank energy features are used with a deep neural
network (GT-DNN) to model robust acoustic event detection (AED) in the smart home …

In the era of smart cities, the advent of the Internet of Things technology has catalyzed the
proliferation of multimodal sensor data, presenting new challenges in cross-modal event …

Noise pollution is one of the major health risks in urban life. The approach to measurement
and identification of noise sources needs to be improved and enhanced to reduce high …

In recent years, there has been an increasing interest in the novel bioinspired sensors,
especially for their selectivity, response time, and sensitivity. Particular attention is paid to …