Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/92559
Title: Iterative classification of regional British accents in i-vector space
Authors: DeMarco, Andrea
Cox, Stephen
Keywords: Natural language processing (Computer science)
Speech processing systems
Machine learning
Automatic speech recognition
Signal processing
Support vector machines
Issue Date: 2012
Publisher: ISCA
Citation: DeMarco, A., & Cox, S. J. (2012). Iterative classification of regional British accents in i-vector space. In Symposium on machine learning in speech and language processing, Oregon. 1-4.
Abstract: Joint-Factor Analysis (JFA) and I-vectors have been shown to be effective for speaker verification and language identification. Channel factor adaptation has also been used for language and accent identification. In this paper, we show how these techniques can be used successfully in the task of accent classification, and we achieve good accuracy on a 14 accent problem using a novel iterative classification framework based on an iterative linear/quadratic classifier. These results compare favourably with recent results obtained using other non-fused acoustic techniques.
URI: https://www.um.edu.mt/library/oar/handle/123456789/92559
Appears in Collections:Scholarly Works - InsSSA

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