The use of qualitative analysis of data to the diagnosis of Dysarthria

There are various kinds of dysarthria, including flaccid, spastic, hyperkinetic, ataxic, hypokinetic, and mixed forms of the illness. In order to determine the specific kind of dysarthria that a patient is struggling with, a speech therapist will examine the patient’s neurological report, administer the Frenchay Dysarthria Assessment (FDA), and listen to the patient speak. The next step is to carry out the techniques that were discussed before in order to see whether i t is possible to determine the kind of dysarthria that a person suffers from. So, in order for the therapist to be able to make an accurate diagnosis of the kind of dysarthria that the patient suffers from, they need to possess both the appropriate degree of training and the essential abilities. The author of this research suggests a technique for detecting dysarthria that takes use of the acoustic characteristics of speech. Some of these characteristics include the fundamental frequency, the formant frequency, and the intensity of speech. The classification is derived from a database of addresses pronounced with a dysarthric accent by persons of Indian heritage who are proficient in English. This information was used to determine the classification. The category of dysarthria is analyzed using a number of different Exploratory Data Analysis (EDA) methods, such as the pair plot, which is a bivariate data analysis method, and t-Distributed Stochastic Neighbor Embedding (t-SNE), which is a multivariate data analysis method. Both of these methods are bivariate and multivariate data analysis methods, respectively. Plotting bivariate and multivariate data may be accomplished using any of these two approaches, respectively. Both the pair plot and the t-SNE approach come to the same conclusions when applied to the data. Both results may be taken as evidence of the same thing.