标题： 歧视损失与SRT：一种基于模型的方法，用于统一语音测试解释 显示英文标题

标题： Discrimination loss vs. SRT: A model-based approach towards harmonizing speech test interpretations

摘要： 目标：语音测试旨在估计分辨损失或语音识别阈值（SRT）。本文研究了从针对分辨损失进行特征描述的临床数据中估计SRT的潜力。了解语音测试结果变量之间的关系——这些变量通过心理物理函数在概念上相关——对于整合不同数据库的数据非常重要。设计：根据可用数据，比较和评估了不同的SRT估计程序。提出了一种新的基于模型的SRT估计程序，该程序处理不完整的患者数据。评估了两种解释模式下的阈上缺陷的解释。研究样本：回顾性分析包括了27009名患者的弗赖堡单音节语音测试（FMST）和听力图（AG）结果，这些结果来自同一天。结果：基于模型的SRT估计程序提供了准确的SRT，但估计斜率存在较大的偏差。两种解释模式下的阈上听力损失成分有所不同。结论：基于模型的程序可用于SRT估计，其特性与个体患者的数据显示有关。所有SRT程序都受到单词识别分数不确定性的干扰。未来，所提出的这种方法可用于评估语音测试之间的其他差异。 显示英文摘要

摘要： Objective: Speech tests aim to estimate discrimination loss or speech recognition threshold (SRT). This paper investigates the potential to estimate SRTs from clinical data that target at characterizing the discrimination loss. Knowledge about the relationship between the speech test outcome variables--conceptually linked via the psychometric function--is important towards integration of data from different databases. Design: Depending on the available data, different SRT estimation procedures were compared and evaluated. A novel, model-based SRT estimation procedure was proposed that deals with incomplete patient data. Interpretations of supra-threshold deficits were assessed for the two interpretation modes. Study sample: Data for 27009 patients with Freiburg monosyllabic speech test (FMST) and audiogram (AG) results from the same day were included in the retrospective analysis. Results: The model-based SRT estimation procedure provided accurate SRTs, but with large deviations in the estimated slope. Supra-threshold hearing loss components differed between the two interpretation modes. Conclusions: The model-based procedure can be used for SRT estimation, and its properties relate to data availability for individual patients. All SRT procedures are influenced by the uncertainty of the word recognition scores. In the future, the proposed approach can be used to assess additional differences between speech tests.