Are speech attractor models useful in diagnosing vocal fold pathologies?
作者信息
Shekofteh Yasser, Gharibzadeh Shahriar, Almasganj Farshad
机构信息
Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran E-mail:
出版信息
J Med Signals Sens. 2013 Jul;3(3):185-6.
Abstract
摘要
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本文引用的文献
1
Support vector wavelet adaptation for pathological voice assessment.支持向量小波自适应用于病理嗓音评估。
Comput Biol Med. 2011 Sep;41(9):822-8. doi: 10.1016/j.compbiomed.2011.06.019. Epub 2011 Jul 20.
2
Identification of voice disorders using long-time features and support vector machine with different feature reduction methods.使用长时特征和支持向量机以及不同特征降维方法识别语音障碍。
J Voice. 2011 Nov;25(6):e275-89. doi: 10.1016/j.jvoice.2010.08.003. Epub 2010 Dec 25.
3
Pathological assessment of patients' speech signals using nonlinear dynamical analysis.使用非线性动力分析对患者语音信号进行病理评估。
Comput Biol Med. 2010 Jan;40(1):54-63. doi: 10.1016/j.compbiomed.2009.10.011. Epub 2009 Dec 5.
4
Telephony-based voice pathology assessment using automated speech analysis.基于电话的语音病理学评估：使用自动语音分析
IEEE Trans Biomed Eng. 2006 Mar;53(3):468-77. doi: 10.1109/TBME.2005.869776.
5
Improvements in estimating the harmonics-to-noise ratio of the voice.语音谐波噪声比估计方法的改进。
J Voice. 1994 Sep;8(3):255-62. doi: 10.1016/s0892-1997(05)80297-8.
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