%0 Journal Article
	%A Dejan Stantic and  Jun Jo
	%D 2012
	%J International Journal of Computer and Systems Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 63, 2012
	%T Accent Identification by Clustering and Scoring Formants
	%U https://publications.waset.org/pdf/5405
	%V 63
	%X There have been significant improvements in automatic
voice recognition technology. However, existing systems still face difficulties,
particularly when used by non-native speakers with accents.
In this paper we address a problem of identifying the English accented
speech of speakers from different backgrounds. Once an accent is
identified the speech recognition software can utilise training set from
appropriate accent and therefore improve the efficiency and accuracy
of the speech recognition system. We introduced the Q factor, which
is defined by the sum of relationships between frequencies of the
formants. Four different accents were considered and experimented
for this research. A scoring method was introduced in order to
effectively analyse accents. The proposed concept indicates that the
accent could be identified by analysing their formants.
	%P 379 - 384