Toward the development of an objective index of dysphonia severity: A four-factor acoustic model
Toward the development of an objective index of dysphonia severity: A four-factor acoustic model
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DOI：
10.1080/02699200400008353
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发表时间：
2006-01-01
影响因子：
1.2
通讯作者：
Roy, N
中科院分区：
文献类型：
--
作者：
Awan, SN;Roy, N
在评估和管理语音障碍患者的过程中，临床医生通常会尝试描述或量化患者发音障碍的严重程度。这项调查使用声学措施来自持续元音样本预测发音困难的严重程度（由听觉感知评级确定），从134名成年女性，有和没有语音障碍的语音样本的不同集合。对所有语音样本进行逐步多元回归分析，然后进行随机和重复交叉验证（随机选择原始134个语音样本语料库的75%; 100次迭代），结果表明，由时间和基于频谱的声学测量组成的四变量模型能够强烈预测发音障碍的感知严重程度（平均R= 0.880;平均R-2= 0.775）。基于倒频谱的测量（CPP/EXP比）被确定为预测发音困难严重程度的最重要因素，尽管很明显，添加其他声学测量（音调σ;闪烁（dB）;和离散傅立叶变换比，低与高频谱能量的测量）大大增加了对严重程度的准确预测。结果进行解释和讨论的关键声学特性，有助于预测的严重性，识别的时间和基于频谱的声学措施，出现敏感的感知不同的声音集的子集的值，以及可能使用的声学模型在指导的听觉感知评级。
During assessment and management of individuals with voice disorders, clinicians routinely attempt to describe or quantify the severity of a patient's dysphonia. This investigation used acoustic measures derived from sustained vowel samples to predict dysphonia severity (as determined by auditory-perceptual ratings), for a diverse set of voice samples obtained from 134 adult females, with and without voice disorders. Stepwise multiple regression analysis on all voice samples, followed by randomized and repeated cross-validation (random selection of 75% of the original 134 voice sample corpus; 100 iterations) indicated that a four-variable model comprised of time and spectral-based acoustic measures was able to strongly predict perceived severity of dysphonia (mean R=.880; mean R-2=.775). A cepstral-based measure (CPP/EXP ratio) was determined to be the most significant contributor to the prediction of dysphonia severity, though it is clear that the addition of other acoustic measures (pitch sigma; shimmer (dB); and the Discrete Fourier Transformation ratio, a measure of low versus high frequency spectral energy) add substantially to the accurate prediction of severity. The results are interpreted and discussed with respect to the key acoustic characteristics that contributed to the prediction of severity, the value of identifying a subset of time and spectral-based acoustic measures which appear sensitive to a perceptually diverse set of voices, and the possible use of acoustic models in guiding auditory-perceptual ratings.