Dejan Stantic and Jun Jo
Accent Identification by Clustering and Scoring Formants
379 - 384
2012
6
3
International Journal of Computer and Systems Engineering
https://publications.waset.org/pdf/5405
https://publications.waset.org/vol/63
World Academy of Science, Engineering and Technology
There have been significant improvements in automatic
voice recognition technology. However, existing systems still face difficulties,
particularly when used by nonnative 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.
Open Science Index 63, 2012