Univ. Lyon, ENTPE, Laboratoire de Tribologie et Dynamique des Systèmes UMR 5513, Rue Maurice Audin, F-69518 Vaulx-en-Velin Cedex, France.
Department of Speech, Language and Hearing Sciences, Boston University, Boston, Massachusetts 02215, USA.
J Acoust Soc Am. 2021 Aug;150(2):1076. doi: 10.1121/10.0005851.
This study aimed at predicting individual differences in speech reception thresholds (SRTs) in the presence of symmetrically placed competing talkers for young listeners with sensorineural hearing loss. An existing binaural model incorporating the individual audiogram was revised to handle severe hearing losses by (a) taking as input the target speech level at SRT in a given condition and (b) introducing a floor in the model to limit extreme negative better-ear signal-to-noise ratios. The floor value was first set using SRTs measured with stationary and modulated noises. The model was then used to account for individual variations in SRTs found in two previously published data sets that used speech maskers. The model accounted well for the variation in SRTs across listeners with hearing loss, based solely on differences in audibility. When considering listeners with normal hearing, the model could predict the best SRTs, but not the poorer SRTs, suggesting that other factors limit performance when audibility (as measured with the audiogram) is not compromised.
本研究旨在预测患有感音神经性听力损失的年轻听众在对称位置存在竞争说话者的情况下的言语接受阈（SRT）的个体差异。现有的双耳模型通过（a）将给定条件下 SRT 的目标语音水平作为输入，以及（b）在模型中引入下限来限制极端负的好耳信噪比，从而进行了修订以处理严重的听力损失。下限值最初是使用静止噪声和调制噪声测量的 SRT 设置的。然后，该模型用于解释使用语音掩蔽器的两个先前发表的数据集中发现的 SRT 个体变化。该模型仅根据可听度的差异很好地解释了听力损失听众的 SRT 变化。当考虑听力正常的听众时，该模型可以预测最佳 SRT，但不能预测较差的 SRT，这表明在可听度（如听力图所示）不受影响的情况下，其他因素限制了性能。
