Parkinson's disease speech detection method based on characteristics of power normalized cepstrum coefficients

Abstract

The invention discloses a Parkinson's disease speech detection method based on characteristics of power normalized cepstrum coefficients. The Parkinson's disease speech detection method solves the problem that Parkinson's disease speech detection is prone to being interfered by noise. The robustness of the extracted characteristics is enhanced through methods such as a Gammatone filter, noise removal and power normalization, and the detection method comprises the following steps that (1) a Parkinson's disease speech library and a healthy speech library are established; (2) characteristics of the power normalized cepstrum coefficients are extracted on a speech signal, specifically, firstly a speech signal is preprocessed, then the Gammatone filter is used for filtering to obtain a speech short-time power spectrum, then the speech short-time power spectrum is weighted and smoothed, and finally the characteristics of the power normalized cepstrum coefficients are calculated; (3) the outerproduct is used for obtaining characteristic vectors; (4) the characteristic vectors are subjected to power and l<2> norm normalization; (5) an SVM is used for training a Parkinson's disease speech model and a healthy speech model; and (6) an SVM classification method is used for classifying, and Parkinson's disease speech detection is realized.

Description

technical field [0001] The invention relates to a method in the technical field of signal processing and pattern recognition, more precisely, the invention relates to a Parkinson's disease speech detection method based on power normalized cepstral coefficient features. Background technique [0002] Parkinson's disease is a common neurodegenerative disease that seriously affects human health. With the intensification of population aging, more and more patients with Parkinson's disease, and there is a trend of younger patients, the situation of diagnosis and treatment of Parkinson's disease is becoming increasingly severe. With the development of time, the symptoms of the disease become more and more serious, and it cannot be completely cured, but early intervention and treatment can relieve symptoms and improve the quality of life of patients. Since the initial symptoms of Parkinson's disease are not obvious, and there is no universally applicable standard that can quickly a...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to overcome the problem of being susceptible to noise interference in Parkinson's disease speech detection, and to provide a Parkinson's disease speech detection method based on power normalized cepstral coefficient features

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