Phoneme-less hierarchical accent classification
Xiaofan Lin, Steven J. Simske · 2005
This paper introduces a novel accent classification method. Compared with existing methods, it has two unique features. First, it does not explicitly utilize phoneme information. Second, it is built on top of the gender classification. We have tested the proposed algorithm on datasets that are completely independent of training data. The accuracy of distinguishing American accent and British accent is 83%. We have also compared the accent classification with the gender classification in terms of accuracy and the saturation behavior with respect to length of utterance.