Rankovic C M
Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, USA.
J Speech Hear Res. 1995 Aug;38(4):913-29. doi: 10.1044/jshr.3804.913.
Hearing aid gain-assignment schemes known as "prescriptions" were not designed for fitting hearing aids that modify their frequency responses to reduce background noise interference. Rather, prescriptions were developed for hearing aids having single, fixed frequency responses and aim to optimize speech reception in relatively quiet environments. Even though prescriptions do not apply to noisy conditions specifically, they embody the trade between maximizing speech audibility and maintaining loudness comfort that is critical to frequency-gain characteristic selection independent of whether noise is present or absent. The articulation index (AI) was used to examine the extent to which prescriptions' deference to loudness comfort causes them to fall short of maximizing speech spectrum audibility, thereby revealing (roughly) the magnitude of the loudness control built into prescriptions. AIs for speech amplified by an AI-maximizing rule (MAX AI) (Rankovic, Freyman, & Zurek, 1992) and according to several prescriptions were calculated as a function of hearing loss degree and configuration for quiet and noisy conditions. In quiet, AIs for prescriptions were similar to one another when presented with the same audiogram but were drastically smaller than MAX AIs, implying that prescriptions limit speech audibility to a large extent to prevent loudness discomfort. In noise, maximizing the AI required frequency-gain characteristics that were substantially different from prescription-assigned characteristics and that were unique to each noise/audiogram combination. A loudness constraint for the MAX AI scheme was developed to account for the gain discrepancy between prescription AIs and MAX AIs observed in the quiet condition, based on the highest comfortable loudness (HCL) equations presented by Cox (1989) in combination with a loudness model (von Paulus & Zwicker, 1972). The MAX AI scheme with the new loudness control was extended to specify frequency-gain characteristics expected to be optimal for several conditions containing noise, and examples are presented.
被称为“处方”的助听器增益分配方案并非为适配能改变其频率响应以减少背景噪声干扰的助听器而设计。相反，这些处方是针对具有单一固定频率响应的助听器制定的，旨在优化在相对安静环境中的语音接收。尽管处方并不专门适用于嘈杂环境，但它们体现了在最大化语音可听度和保持响度舒适度之间的权衡，这对于独立于噪声是否存在的频率增益特性选择至关重要。清晰度指数（AI）被用于检验处方对响度舒适度的考量在多大程度上导致它们未能最大化语音频谱可听度，从而大致揭示处方中内置的响度控制程度。根据AI最大化规则（MAX AI）（Rankovic、Freyman和Zurek，1992年）以及几种处方放大的语音的清晰度指数，被计算为安静和嘈杂环境下听力损失程度和配置的函数。在安静环境中，当呈现相同听力图时，各处方的清晰度指数彼此相似，但远小于MAX AI，这意味着处方在很大程度上限制了语音可听度以防止响度不适。在噪声环境中，最大化清晰度指数所需的频率增益特性与处方分配的特性有很大不同，并且对于每种噪声/听力图组合都是独特的。基于Cox（1989年）提出的最高舒适响度（HCL）方程并结合响度模型（von Paulus和Zwicker，1972年），为MAX AI方案制定了响度约束，以解释在安静条件下观察到的处方清晰度指数和MAX AI之间的增益差异。具有新响度控制的MAX AI方案被扩展，以指定预期在几种包含噪声的条件下最优的频率增益特性，并给出了示例。
