| 基于非线性动力学和GMM的病态嗓音识别与研究 |
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| 引用本文： | 高俊芬,胡维平. 基于非线性动力学和GMM的病态嗓音识别与研究[J]. 广西师范大学学报(自然科学版), 2011, 29(3): 5-8 |
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| 作者姓名： | 高俊芬 胡维平 |
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| 作者单位： | 广西师范大学电子工程学院,广西桂林,541004 |
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| 基金项目： | 广西自然科学基金资助项目(2010GXNSFA013128) |
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| 摘 要： | 本文采用非线性动力学的分析方法,定量分析并提取了正常与病态嗓音的5维非线性特征:Hurst参数、香农熵、计盒维数、Kolmogorov熵和关联维数；使用来源于临床病例的151例数据,选用高斯混合模型GMM (gaussian mixture model)的模式识别方法,来评估基于非线性动力学分析方法所提取的特征参数的有...
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| 关 键 词： | 非线性动力学 GMM 混沌理论 病态嗓音 |
Recognition and Study of Pathological Voices Based on Nonlinear Dynamics Using GMM |
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| GAO Jun-fen,HU Wei-ping. Recognition and Study of Pathological Voices Based on Nonlinear Dynamics Using GMM[J]. Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(3): 5-8 |
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| Authors: | GAO Jun-fen HU Wei-ping |
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| Affiliation: | GAO Jun-fen,HU Wei-ping(College of Electronic Engineering,Guangxi Normal University,Guilin Guangxi 541004,China) |
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| Abstract: | The method of nonlinear dynamics analysis is used to quantitatively analyze and extract the normal and pathological voice of the 5-dimensional nonlinear feature,Hurst parameter,Shannon entropy,box dimension,Kolmogorov entropy and correlation dimension.The data is from the clinical cases of 151 patients and the pattern recognition method of Gaussian mixture model is used to evaluate the validity of the parameters extracted by the method of nonlinear dynamics.Experimental results show that this method can com... |
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| Keywords: | nonlinear dynamics GMM chaos theory pathological voices |
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