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Detection of various diseases by using formant track extraction and pitch contour analysis

机译:通过共振峰轨迹提取和音高轮廓分析检测各种疾病

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摘要

Pitch and formant are two of the most important characteristics of voice signals. These features can be analyzed to detect the condition of patients having Obstructive Sleep Apnea Syndrome (OSAS) and Unilateral Vocal Cord Paralysis (UVCP) before or after treatment. In this paper, we propose a method to determine whether the patients have healed from the disease or not, by using formants track extraction and pitch contour analysis. The formant frequencies are computed by using Linear Predictive Coding (LPC) method and the pitch frequencies are determined by the same LPC & calculating the real cepstrum of the voice signals. A total of 2 patients, one having OSAS and one having UVCP, were analyzed. Significant differences are found in the variation of formant frequencies of both groups. The formant frequencies of patients are higher than the formant frequencies of normal subject and the pitch frequencies are inconsistently unstable than the normal subject. The results are commended from the view of pathophysiological aspect.
机译:音调和共振峰是语音信号最重要的两个特征。可对这些特征进行分析,以检测治疗前后的阻塞性睡眠呼吸暂停综合症(OSAS)和单侧声带麻痹(UVCP)的患者状况。在本文中,我们提出了一种通过使用共振峰轨迹提取和音高轮廓分析来确定患者是否已从疾病中治愈的方法。通过使用线性预测编码(LPC)方法计算共振峰频率,并通过相同的LPC并计算语音信号的真实倒谱来确定音高频率。分析了总共2例患者,其中1例患有OSAS,1例患有UVCP。两组共振峰频率的变化存在显着差异。患者的共振峰频率高于正常受试者的共振峰频率,并且基音频率始终比正常受试者不稳定。从病理生理方面来看,该结果值得称赞。

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