Dysarthria identifying method, system and device

Abstract

The invention provides a dysarthria identifying method. The dysarthria identifying method includes the steps that sample data are acquired, calibrated and denoised, wherein the sample data comprise the voice data and the organ motion data; the resonance peak value of the voice data is extracted, and sample acoustic parameters are calculated; the tongue and lip deviation displacement of the organ motion data is calculated; sample kinematics parameters of the organ motion data are calculated; correlation calculation is carried out on the resonance peak value and the tongue and lip deviation displacement, and multiple regression calculation is carried out on the sample acoustic parameters and the sample kinematics parameters to obtain a regression equation; collected data are acquired, and target kinematics parameters are calculated according to the regression equation; the collected data are identified and classified according to the sample kinematics parameters and the target kinematics parameters. Dysarthria identifying accuracy can be effectively improved by the adoption of the method. The invention further provides a dysarthria identifying device and system.

Description

technical field [0001] The invention relates to the field of speech aids, in particular to a method, device and system for identifying dysarthria. Background technique [0002] With the development of society, the role of language communication between people is becoming more and more important in all aspects of social life, so many problems in the process of language communication have also been paid more and more attention. Among them, dysarthria is the most common language disorder, which seriously affects daily communication and normal psychological development of patients. Practice has proved that the effect of language training on patients with dysarthria is better, and the key to voice training is to accurately evaluate patients, so it is very important to find out the difference and characteristics of pronunciation between patients and normal people and to conduct accurate and effective evaluation significance. [0003] At present, the methods for detecting and eva...

AI Technical Summary

Problems solved by technology

[0004] However, the disadvantage of acoustic parameter assessment is that it is not yet known whether the formant can completely replace the real tongue movement data of the patient when speaking. Therefore, the accuracy of detecting and evaluating dysarthria based on the acoustic parameters calculated from the formant is not high.

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