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首页> 外文期刊>Journal of computational and theoretical nanoscience >Classification of Pathological Voices Using Glottal Signal Parameters
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Classification of Pathological Voices Using Glottal Signal Parameters

机译:使用光学信号参数进行病理声音的分类

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摘要

The discrimination of voice signals has numerous applications in diagnosing of pathologies related to voice. This paper discussed about the glottal signal that is bound to recognize two sorts of voice issue: Laryngitis and Laryngeal dystonia (LD). The parameters of the glottal signalfill in as contribution to classifiers that characterizes into three unique gatherings of speakers: speakers with Laryngitis; with laryngeal dystonia (LD); lastly speakers with healthy voices. The database is made out of voice accounts containing tests of three gatherings. The classifiersSVM provided 60%, KNN provided 70% and Ensemble provided 80% classification accuracy in the case of Laryngitis. Voice signals of patients affected with Laryngeal dystonia were also collected and tested with same classifiers and the Accuracy of 90%, 80% and 50% were obtained with SVM, KNN andEnsemble respectively.
机译:语音信号的辨别在诊断与语音相关的病理学方面具有许多应用。 本文讨论了旨在识别两种语音问题的声门信号:喉炎和喉肌(LD)。 光门信号填埋的参数作为对分类器的贡献,以表征成三个独特的扬声器聚集:喉炎的扬声器; 喉部肌腹(LD); 最后发言者具有健康的声音。 数据库由包含三个聚会的测试的语音帐户制成。 提供60%,KNN提供的分类器,提供70%和合奏在喉炎的情况下提供了80%的分类准确性。 还收集了喉部肌瘤的患者的语音信号,并用相同的分类器测试,用SVM,KNN和等酶获得90%,80%和50%的准确度。

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