Cluster of Excellence "Hearing4all," Department für Medizinische Physik und Akustik, Carl-von-Ossietzky Universität Oldenburg, Carl-von Ossietzky-Strasse 9-11, D-26111 Oldenburg, Germany.
J Acoust Soc Am. 2014 Mar;135(3):1506-17. doi: 10.1121/1.4864293.
Consonant recognition was assessed in normal-hearing (NH) and hearing-impaired (HI) listeners in quiet as a function of speech level using a nonsense logatome test. Average recognition scores were analyzed and compared to recognition scores of a speech recognition model. In contrast to commonly used spectral speech recognition models operating on long-term spectra, a "microscopic" model operating in the time domain was used. Variations of the model (accounting for hearing impairment) and different model parameters (reflecting cochlear compression) were tested. Using these model variations this study examined whether speech recognition performance in quiet is affected by changes in cochlear compression, namely, a linearization, which is often observed in HI listeners. Consonant recognition scores for HI listeners were poorer than for NH listeners. The model accurately predicted the speech reception thresholds of the NH and most HI listeners. A partial linearization of the cochlear compression in the auditory model, while keeping audibility constant, produced higher recognition scores and improved the prediction accuracy. However, including listener-specific information about the exact form of the cochlear compression did not improve the prediction further.
正常听力 (NH) 和听力障碍 (HI) 受试者在安静环境下使用无意义音节测试，评估其在不同语音水平下的辅音识别能力。分析平均识别分数，并与语音识别模型的识别分数进行比较。与常用的基于长时频谱的频谱语音识别模型不同，本研究使用了一种在时域中运行的“微观”模型。测试了该模型的变体（考虑听力障碍）和不同的模型参数（反映耳蜗压缩）。使用这些模型变体，本研究检验了在安静环境下的语音识别性能是否受到耳蜗压缩变化的影响，即 HI 受试者中经常观察到的线性化。HI 受试者的辅音识别分数比 NH 受试者差。该模型准确预测了 NH 和大多数 HI 受试者的语音接受阈值。在听觉模型中对耳蜗压缩进行部分线性化，同时保持可听度不变，可提高识别分数并提高预测准确性。然而，包括关于耳蜗压缩的确切形式的听众特定信息并不能进一步提高预测精度。
