Kopf Lisa M, Jackson-Menaldi Cristina, Rubin Adam D, Skeffington Jean, Hunter Eric J, Skowronski Mark D, Shrivastav Rahul
Department of Communicative Sciences and Disorders, Michigan State University, East Lansing, Michigan; Department of Communication Sciences and Disorders, University of Iowa, Iowa City, Iowa.
Department of Communicative Sciences and Disorders, Michigan State University, East Lansing, Michigan; Lakeshore Professional Voice Center, Lakeshore Ear, Nose, and Throat Center, St. Clair Shores, Michigan; Department of Otolaryngology, School of Medicine, Wayne State University, Detroit, Michigan.
J Voice. 2017 Nov;31(6):691-696. doi: 10.1016/j.jvoice.2017.01.016. Epub 2017 Mar 17.
Measurement of treatment outcomes is critical for the spectrum of voice treatments (ie, surgical, behavioral, or pharmacological). Outcome measures typically include visual (eg, stroboscopic data), auditory (eg, Consensus Auditory-Perceptual Evaluation of Voice; Grade, Roughness, Breathiness, Asthenia, Strain), and objective correlates of vocal fold vibratory characteristics, such as acoustic signals (eg, harmonics-to-noise ratio, cepstral peak prominence) or patient self-reported questionnaires (eg, Voice Handicap Index, Voice-Related Quality of Life). Subjective measures often show high variability, whereas most acoustic measures of voice are only valid for signals where some degree of periodicity can be assumed. However, this assumption is often invalid for dysphonic voices where signal periodicity is suspect. Furthermore, many of these measures are not useful in isolation for diagnostic purposes.
We evaluated a recently developed algorithm (Auditory Sawtooth Waveform Inspired Pitch Estimator-Prime [Auditory-SWIPE']) for estimating pitch and pitch strength for dysphonic voices. Whereas fundamental frequency is a physical attribute of a signal, pitch is its psychophysical correlate. As such, the perception of pitch can extend to most signals irrespective of their periodicity.
Post hoc analyses were conducted for three groups of patients evaluated and treated for voice problems at a major voice center: (1) muscle tension dysphonia/functional dysphonia, (2) vocal fold mass(es), and (3) presbyphonia. All patients were recorded before and after surgical/behavioral treatment for voice disorders. Pitch and pitch strength for each speaker were computed with the Auditory-SWIPE' algorithm.
Comparison of pre- and posttreatment data provides support for pitch strength as a measure of treatment outcomes for dysphonic voices.
治疗效果的测量对于嗓音治疗的各个方面（即手术、行为或药物治疗）至关重要。疗效指标通常包括视觉指标（如频闪数据）、听觉指标（如嗓音的共识听觉-感知评估；等级、粗糙度、气息声、无力感、紧张度）以及声带振动特征的客观相关指标，如声学信号（如谐波噪声比、谐波峰值突出度）或患者自我报告问卷（如嗓音障碍指数、嗓音相关生活质量）。主观指标往往显示出高度变异性，而大多数嗓音声学指标仅对可假定具有一定程度周期性的信号有效。然而，对于嗓音障碍患者的嗓音，信号周期性存疑，这一假设往往不成立。此外，这些指标中的许多单独用于诊断目的时并无用处。
我们评估了一种最近开发的算法（听觉锯齿波形启发的基频估计器-升级版[听觉-SWIPE']），用于估计嗓音障碍患者的基频和基频强度。虽然基频是信号的物理属性，但基频强度是其心理物理相关指标。因此，基频强度的感知可以扩展到大多数信号，而不论其周期性如何。
对在一个主要嗓音中心接受嗓音问题评估和治疗的三组患者进行了事后分析：（1）肌肉紧张性发音障碍/功能性发音障碍，（2）声带肿物，（3）老年嗓音障碍。所有患者在接受嗓音疾病的手术/行为治疗前后均进行了录音。使用听觉-SWIPE'算法计算每个说话者的基频和基频强度。
治疗前和治疗后数据的比较为基频强度作为嗓音障碍患者治疗效果的指标提供了支持。
