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Automatic Detection of Hypernasality in Children

机译:自动检测儿童鼻涕

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摘要

Automatic hypernasality detection in children with Cleft Lip and Palate is made considering five Spanish vowels. Characterization is performed by means of some acoustic and noise features, building a representation space with high dimensionality. Most relevant features are selected using Principal Components Analisis and linear correlation in order to enable clinical interpretation of results and achieving spaces with lower dimensions per vowel. Using a Linear-Bayes classifier, success rates between 80% and 90% are reached, beating success rates achived in similiar studies recently reported.
机译:考虑到五个西班牙元音,对唇裂和Pal裂患儿进行自动鼻音检测。通过一些声学和噪声特征进行表征,从而构建具有高维的表示空间。使用主成分分析和线性相关来选择最相关的特征,以便能够对结果进行临床解释并获得每个元音尺寸较小的空间。使用线性贝叶斯分类器,成功率达到80%至90%,超过了最近报道的类似研究中获得的成功率。

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