4 accepted papers
SONAR technology plays a pivotal role in terrain exploration and specifically identification of objects of interest. However, it grapples with a recurring challenge of clutter and noise which limits the performance of target recognition models. The challenge of noisy observations renders the choice…
Sound Event Detection (SED) tackles the challenge of identifying sound events in an audio recording by delimiting both their temporal boundaries as well as sound category. With recent advances in deep learning, current systems are able to leverage availability of large datasets to train sophisticate…
Sound event detection (SED) takes on the task of identifying presence of specific sound events in a complex audio recording. SED has tremendous implications in video analytics, smart speaker algorithms and audio tagging. Recent advances in deep learning have afforded remarkable advances in performan…
In this paper, a novel feature for noise robust sound event recognition is proposed. The proposed feature is obtained by a two-step procedure. First, a subspace bank is established via target event analysis in complex vector space. Then, by projecting observation vectors onto the subspace bank, nois…