Acoustic analysis is commonly used to diagnose, document and treat voice disorders. Type I and Type II voices which are nearly periodic can be easily assessed with computerised acoustic analysers. Widely used voice parameters like Jitter, Shimmer and Harmonic Noise Ratio (HNR) are indices of voice pathology and indicate different diseases and help as an outcome measure.Aim: To study whether objective acoustic analysis is able to differentiate between abnormal and normal voices.Materials and Methods: In the present study, the patients were made to phonate sustained vowel /a/ and the voice was recorded to analyse parameters like Jitter (ddp), Shimmer (dda), HNR and Median pitch using the acoustic software, PRAAT. These parameters were compared with the values of the institute?s own normal voice database. They were analysed for Mean, Median, standard error of mean, and Kolmogorov-Smironov values.Results: The range of abnormal voice parameters like Jitter (ddp), shimmer (dda), median pitch and HNR measures were different from normal voices. The difference was significant in jitter (p-value of 0.026) in males, in Shimmer (p-value of 0.035) in females. HNR did not show any significance.Conclusion: The traditional methods of perturbation measures like Jitter, Shimmer, Median pitch and HNR can help the clinicians for characterisation of voice into either normal or abnormal voices. But the comparison needs a local or regional normal voice database.
展开▼
机译：声学分析通常用于诊断，记录和治疗语音障碍。使用计算机声学分析仪可以轻松评估几乎为周期性的I型和II型语音。广泛使用的语音参数（如抖动，闪光和谐波噪声比（HNR））是语音病理学的指标，可以指示不同的疾病，并可以作为结果度量。目的：研究客观声学分析是否能够区分异常和正常材料和方法：在本研究中，让患者发声持续元音/ a /，并记录声音以分析参数，例如抖动（ddp），闪光（dda），HNR和中音。声学软件PRAAT。将这些参数与研究所自己的正常语音数据库的值进行比较。对它们进行了均值，中位数，均值标准误差和Kolmogorov-Smironov值的分析。结果：异常语音参数（如抖动（ddp），微光（dda），中音和HNR量度）的范围与正常值不同声音。男性的抖动（p值为0.026），女性的微光（p值为0.035）差异显着。 HNR没有任何意义。结论：抖动，微光，中值音高和HNR等传统的摄动测量方法可以帮助临床医生将声音表征为正常或异常声音。但是比较需要本地或区域正常语音数据库。
展开▼
