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Voice pathology classification based on High-Speed Videoendoscopy

机译:基于高速视频视觉镜检查的语音病理分类

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This work presents a method for automatical and objective classification of patients with healthy and pathological vocal fold vibration impairments using High-Speed Videoendoscopy of the larynx. We used an image segmentation and extraction of a novel set of numerical parameters describing the spatio-temporal dynamics of vocal folds to classification according to the normal and pathological cases and achieved 73,3% cross-validation classification accuracy. This approach is promising to develop an automatic diagnosis tool of voice disorders.
机译:本作品介绍了使用喉部高速视频镜检查的健康和病理声带振动损伤患者的自动和客观分类方法。我们使用了一种新颖的数值参数的图像分割和提取,描述了语言折叠的时空动态,根据正常和病理情况,实现了73,3%的交叉验证分类精度。这种方法很有希望开发语音障碍的自动诊断工具。

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