Identification of Pronunciation Defects in Spoken Arabic Language

Abstract

The detection of vocal pathologies is one of the novelties addressing automatic speech processing. There are several intervening approaches that are based on features contained in an acoustic signal and on natural language processing techniques. However, up to our knowledge, these studies are not extended to detect phonemes that pose degraded speeches. In this paper, we propose a new method to detect mispronounced sounds. We are based on a phonetic-probabilistic modeling. The invented study accounts four fundamental tasks. The first task summarizes the calculation of the probabilistic-phonetic model referring to Arabic speech. The second one is dedicated to calculate the probabilistic-phonetic model appropriate to a speaker whose elocution is classified as pathological. Thirdly, we compare between the two previous models to distinguish two main classes: the input speech can be healthy or pathological. The fourth stage consists in introducing an original algorithm based on a phonetic modeling to generate problematic sounds and to evaluate the elocution of each speaker having voice pathologies by attributing them a language level. This task will be only applied if the input speech is pathological. The obtained results are satisfactory. We have attained a problematic-sound identification rate of 96%.