Evaluation of syllable stress using single class classifier

Evaluation of syllable stress in speech utterances is an important and challenging task in the area of speaker evaluation. In this paper, we propose a method to classify correct utterances of English words based on the evaluation of the lexical syllable stress pattern. Here we use only correctly stressed utterances of the words as training samples since a statistically significant pool of incorrectly stressed utterances is difficult to obtain. The underlying assumption here is that the correct utterances of a word form a compact cluster or a collection of compact clusters (with speaker dependent variations) in a suitably chosen multi-dimensional attribute space. We experimentally demonstrate the effectiveness of the proposed method on several English words and also compare with the standard classifiers where samples from both correct and incorrect utterances were used.