A Systematic Review of Machine Learning based Automatic Speech Assessment System to Evaluate Speech Impairment

Aphasia is a communication disability that falls under the category of neurological speech disorder. The main cause of the aphasia individual speech impairment damages certain portion of the cerebrum. The aphasic speech impairment ranges from mild level to the extreme level of severity in which the individual will not be able to communicate. The aphasia individuals face difficulties on the different communication categories like some individual have difficulty in formation of the clear and meaningful sentence, some have problem with understanding and some have trouble in the reading process. The aphasic speech impairment experience will be unique for each individual. It purely depends on the portion of the impairment in the cerebrum, position of the impairment in brain, degree of the severity and also individual age factor. This research work focuses on the assessment of speech impairment in the aphasia patients, basically in order to evaluate the communication aptitude of the aphasia individual. The assessment approach is based on the analysis of factors related to speech such as articulation, phonation, prosody and intelligibility. Through the assessment approach, degree of the severity level of patient will be identified through the automatic speech recognition (ASR) methodologies. This work helps the medical examiners namely neurologists and speech therapists to perform the effective speech analysis for the individuals with aphasia speech disorder.