Previous accent classification research focused mainly on detecting accents
with pure acoustic information without recognizing accented speech. This work
combines phonetic knowledge such as vowels with acoustic information to build
Guassian Mixture Model (GMM) classifier with Perceptual Linear Predictive (PLP)
features, optimized by Hetroscedastic Linear Discriminant Analysis (HLDA). With
input about 20-second accented speech, this system achieves classification rate
of 51% on a 7-way classification system focusing on the major types of accents
in English, which is competitive to the state-of-the-art results in this field.