A New E-Health Tool For Early Identification Of Voice And Neurological Pathologies By Speech Processing

The objective of this study is to develop a non-invasive method of early identification and classification of voice pathologies and neurological diseases by speech processing. We will present a new automatic medical diagnosis tool which can assist specialists in their medical diagnosis. The developed strategy is based on speech acquisition of the patient followed by audio features extraction, training and recognition by using the HTK toolkit. The computed parameters are compared to standard values from a codebook database. The experiments and tests are conducted by using the MEEI pathological database of KEY Pentax. The obtained results give good discrimination with a mean pathology recognition ratio about 95%. Finally, this E-Health application is helpful for the prevention of specific diseases and improving the quality of patient care as well as reducing the costs of healthcare.