Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.422904
Title: Phase as a feature extraction tool for audio classification and signal localisation
Author: Paraskevas, Ioannis
ISNI:       0000 0001 3467 2321
Awarding Body: University of Surrey
Current Institution: University of Surrey
Date of Award: 2005
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Abstract:
The aim of this research is to demonstrate the significance of signal phase content in time localization issues in synthetic signals and in the extraction of appropriate features from acoustically similar audio recordings (non-synthetic signals) for audio classification purposes. Published work, relating to audio classification, tends to be1 focused on the discrimination of audio classes that are dissimilar acoustically. Consequently, a wide range of features, extracted from the audio recordings, has been appropriate for the classification task. In this research, the audio classification application involves audio recordings (digitized through the same pre-processing conditions) that are acoustically similar and hence, only a few features are appropriate, due to the similarity amongst the classes. The difficulties in processing the phase spectrum of a signal have probably led previous researchers to avoid its investigation. In this research, the sources of these difficulties are studied and certain methods are employed to overcome them. Subsequently, the phase content of the signal has been found to be useful for various applications. The justification of this, is demonstrated via audio classification (non-synthetic signals) and time localization (synthetic signals) applications. Summarizing, the original contributions, introduced based on this research work, are the 'whitened' Hartley spectrum and its short-time analysis, as well as the use of the Hartley phase cepstrum as a time localization tool and the use of phase related feature vectors for the audio classification application.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.422904  DOI: Not available
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