摘要
目的 探讨嗓音的客观多参数检测与主观听觉评估的相关性 ,建立嗓音客观多参数评估模式 ,实现嗓音评估的客观化、数据化。方法 声音样本采自 135例声音嘶哑患者和 2 9例嗓音正常者。客观检测采用法国开发的“EVA ”嗓音工作站 ,测试对象发长元音 /α :/时 ,检测下列参数 :基频 (F0 )、音强 (intensity)、基频微扰 (jitter)、信噪比 (signal-to -noiseratio ,SNR)、Lyapunov系数、口腔气流量 (oralairflow ,OAF)、音域 (range)及最大发声时间 (maxi mumphonatorytime,MPT) ;发 /pα/音时 ,检测声门下压 (estimatedsubglotticpressure ,ESGP)。主观听觉评估采用日本言语语音学会声音嘶哑评估GRBAS系统中的总嘶哑度 (grade,G) 4级评估标准。所有受试者以自然的音调及音强读一段统一的标准文字 ,听评委由 4名嗓音学家组成。结果 应用判别分析方法 ,建立了 7参数客观评估模式 (音域、Lyapunov系数、声门下压、最大发声时间、口腔气流量、信噪比和基频 )。客观评估结果与主观评估结果的一致性达到 84 %。结论 嗓音的客观检测是多参数的 。
Objective To develop a multi-parametric objective evaluation protocol and investigate its correlation with perceptual analysis of continuous speech for objectivity and quantitatively. Methods The voice samples were collected from 135 patients with dysphonia and 29 subjects with normal voice. The objective parameters, including fundamental frequency (F 0), intensity, jitter, signal-to-noise ratio, Lyapunov coefficient (LC),oral airflow (OAF), vocal range (Range) and maximum phonatory time (MPT) which were measured mainly on a sustained /a/ and estimated subglottic pressure (ESGP) which was determined on a series of /pa/,were recorded on an 'EVA' workstation which was developed in French. According to the G (overall dysphonia) component of the GRBAS score on a 4-point scale ranging from 0 for normal to 3 for severe dysphonia, the perceptual analysis was done by a jury composed of 4 experienced listeners and the voice samples (continuous speech) were from the same patients with normal voices and normal intensity. Results Using the discriminate analysis, a seven parameters protocol (Range, LC, ESGP, MPT, OAF, signal-to-noise ratio and F 0) was developed. Result showed that this protocol allowed 84% concordance with jury classification.Conclusion The objective voice evaluation is multi-parametric and is able to reflet the result of perceptual analysis.
出处
《听力学及言语疾病杂志》
CAS
CSCD
2003年第3期161-164,共4页
Journal of Audiology and Speech Pathology
关键词
嗓音
客观多参数分析
主观听觉分析
相关性
评估模式
Voice objective Multi-parametric analysis Perceptual analysis Discriminate analysis