Acoustic scene classification using time-frequency representations as texture images

Shamsiah Abidin

Research output: ThesisDoctoral Thesis

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Abstract

Acoustic scene classification (ASC) is important for context-aware applications to recognise the environment based on the available acoustic information. Despite its promising application prospects, ASC is a challenging problem due to both the similar characteristics of some scenes and complexity of sounds present in other scenes. This dissertation presents findings in the field of ASC utilising hand-crafted visually inspired features extracted from a 2D time-frequency image representation. The time-­frequency visual representations of the temporal and spectral structures for each acoustic scene with suitable feature extraction methods were shown to enhance the identification of the different scene classes.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • The University of Western Australia
Award date30 Oct 2019
DOIs
Publication statusUnpublished - 2019

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