A Novel Approach to Identify Factor Posing Pronunciation Disorders

Literature seems rich with approaches which are based on the features contained in the speech signal and natural language processing techniques to detect vocal pathologies in human speeches. From the literature, we can mention also that several factors (vocal pathology, non-native speaker, psychological state, age …) can pose pronunciation disorders [10]. But to our knowledge, no work has treated pathological speech to identify factor posing pronunciation disorders. The current work consists in introducing an original approach based on the forced alignment score [8] to identify the factor posing mispronunciations contained in the Arabic speech. We distinguish two main factors: the pronunciation disorders can be from native speakers with vocal pathology or from non-native speakers who do not master Arabic-phoneme pronunciation. The results are encouraging; we attain an identification rate of 95 %. Biologists and computer scientists can benefit from our proposed approach to design high performance systems of vocal pathology diagnostic.