Parkinson's disease speech data classification system based on dbn and rf algorithms

A speech data, Parkinson's disease technology, applied in the field of intelligent classification algorithm, can solve the problem of lack of nonlinear feature processing ability and so on

Active Publication Date: 2021-04-27
CHONGQING UNIV
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Problems solved by technology

[0003] Based on the current technology, the diagnosis method based on voice data is more effective, so some researchers have designed a classification algorithm based on voice to diagnose PD, but when performing feature extraction, most of them use linear transformation, which lacks nonlinearity. feature processing capability

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  • Parkinson's disease speech data classification system based on dbn and rf algorithms
  • Parkinson's disease speech data classification system based on dbn and rf algorithms
  • Parkinson's disease speech data classification system based on dbn and rf algorithms

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Embodiment Construction

[0023] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will describe in detail with reference to the drawings and specific embodiments.

[0024] A Parkinson's disease speech data classification system based on DBN and RF algorithms, including:

[0025] Voice data input module, for collecting the voice data of the patient to be tested;

[0026] The classification recognizer is used to classify and recognize the speech data. The classification recognizer includes a feature transformation module based on the DBN deep belief network and a classifier based on the RF random forest algorithm, and achieves a predetermined level by training and testing the original sample data set standards of eligibility;

[0027] The output module is used to output classification recognition results.

[0028] Such as figure 1 As shown, in the specific implementation process, the classification recognizer need...

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Abstract

The invention discloses a speech data classification system for Parkinson's disease based on DBN and RF algorithms, which is characterized in that it comprises: a speech data input module for collecting the speech data of a patient to be tested; a classification recognizer for classifying the speech data Perform classification recognition, the classification recognizer includes a feature transformation module based on the DBN deep belief network and a classifier based on the RF random forest algorithm, and reaches the preset qualification standard through original sample data training and testing; the output module is used to output classification recognition results. The effect is: DBN is introduced into the Parkinson's disease speech data classification system, and better features are introduced through nonlinear transformation, thereby obtaining more satisfactory accuracy and ensuring the accuracy of Parkinson's disease diagnosis.

Description

technical field [0001] The invention relates to an intelligent classification algorithm in biomedical information processing, in particular to a Parkinson's disease voice data classification system based on DBN and RF algorithms. Background technique [0002] Parkinson's disease (PD) is a neurodegenerative disease of the central nervous system, symptoms mainly include tremor, stiffness, loss of muscle control, slow movement, poor balance and speech problems. So far, the disease has affected nearly 10 million people around the world, and China is also a high-incidence area of ​​Parkinson's disease. High-quality biomarkers are the key to the diagnosis and treatment of Parkinson's disease. Unfortunately, reliable PD biomarkers have not yet been identified. However, recent research has shown that speech signals (data) can help identify patients with Parkinson's disease from healthy people, since the vast majority of patients usually exhibit some degree of dysarthria. [0003]...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G10L15/08
CPCG10L15/08G10L15/083
Inventor 李勇明肖洁王品谢廷杰郑源林张小恒颜芳
Owner CHONGQING UNIV
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