Bernstein Joshua G W, Mehraei Golbarg, Shamma Shihab, Gallun Frederick J, Theodoroff Sarah M, Leek Marjorie R
Audiology and Speech Center, Scientific and Clinical Studies Section, Walter Reed National Military Medical Center, Bethesda, MD, USA.
J Am Acad Audiol. 2013 Apr;24(4):293-306. doi: 10.3766/jaaa.24.4.5.
A model that can accurately predict speech intelligibility for a given hearing-impaired (HI) listener would be an important tool for hearing-aid fitting or hearing-aid algorithm development. Existing speech-intelligibility models do not incorporate variability in suprathreshold deficits that are not well predicted by classical audiometric measures. One possible approach to the incorporation of such deficits is to base intelligibility predictions on sensitivity to simultaneously spectrally and temporally modulated signals.
The likelihood of success of this approach was evaluated by comparing estimates of spectrotemporal modulation (STM) sensitivity to speech intelligibility and to psychoacoustic estimates of frequency selectivity and temporal fine-structure (TFS) sensitivity across a group of HI listeners.
The minimum modulation depth required to detect STM applied to an 86 dB SPL four-octave noise carrier was measured for combinations of temporal modulation rate (4, 12, or 32 Hz) and spectral modulation density (0.5, 1, 2, or 4 cycles/octave). STM sensitivity estimates for individual HI listeners were compared to estimates of frequency selectivity (measured using the notched-noise method at 500, 1000, 2000, and 4000 Hz), TFS processing ability (2 Hz frequency-modulation detection thresholds for 500, 1000, 2000, and 4000 Hz carriers) and sentence intelligibility in noise (at a 0 dB signal-to-noise ratio) that were measured for the same listeners in a separate study.
Eight normal-hearing (NH) listeners and 12 listeners with a diagnosis of bilateral sensorineural hearing loss participated.
STM sensitivity was compared between NH and HI listener groups using a repeated-measures analysis of variance. A stepwise regression analysis compared STM sensitivity for individual HI listeners to audiometric thresholds, age, and measures of frequency selectivity and TFS processing ability. A second stepwise regression analysis compared speech intelligibility to STM sensitivity and the audiogram-based Speech Intelligibility Index.
STM detection thresholds were elevated for the HI listeners, but only for low rates and high densities. STM sensitivity for individual HI listeners was well predicted by a combination of estimates of frequency selectivity at 4000 Hz and TFS sensitivity at 500 Hz but was unrelated to audiometric thresholds. STM sensitivity accounted for an additional 40% of the variance in speech intelligibility beyond the 40% accounted for by the audibility-based Speech Intelligibility Index.
Impaired STM sensitivity likely results from a combination of a reduced ability to resolve spectral peaks and a reduced ability to use TFS information to follow spectral-peak movements. Combining STM sensitivity estimates with audiometric threshold measures for individual HI listeners provided a more accurate prediction of speech intelligibility than audiometric measures alone. These results suggest a significant likelihood of success for an STM-based model of speech intelligibility for HI listeners.
对于给定的听力受损(HI)听众,一个能够准确预测言语可懂度的模型将是助听器验配或助听器算法开发的重要工具。现有的言语可懂度模型没有纳入超阈值缺陷的变异性,而经典听力测试方法无法很好地预测这些缺陷。纳入此类缺陷的一种可能方法是基于对同时进行频谱和时间调制信号的敏感度来进行可懂度预测。
通过比较一组HI听众的频谱时间调制(STM)敏感度估计值与言语可懂度以及频率选择性和时间精细结构(TFS)敏感度的心理声学估计值,评估这种方法成功的可能性。
针对时间调制率(4、12或32赫兹)和频谱调制密度(0.5、1、2或4周期/倍频程)的组合,测量检测应用于86分贝声压级四分之一倍频程噪声载波的STM所需的最小调制深度。将个体HI听众的STM敏感度估计值与频率选择性估计值(使用陷波噪声法在500、1000、2000和4000赫兹处测量)、TFS处理能力(500、1000、2000和4000赫兹载波的2赫兹频率调制检测阈值)以及在单独研究中为相同听众测量的噪声环境下句子可懂度(在0分贝信噪比下)进行比较。
八名听力正常(NH)的听众和12名被诊断为双侧感音神经性听力损失的听众参与了研究。
使用重复测量方差分析比较NH和HI听众组之间的STM敏感度。逐步回归分析将个体HI听众的STM敏感度与听力阈值、年龄以及频率选择性和TFS处理能力的测量值进行比较。第二步逐步回归分析将言语可懂度与STM敏感度以及基于听力图的言语可懂度指数进行比较。
HI听众的STM检测阈值升高,但仅在低调制率和高密度时出现。4000赫兹处的频率选择性估计值和500赫兹处的TFS敏感度估计值相结合,可以很好地预测个体HI听众的STM敏感度,但与听力阈值无关。STM敏感度在基于可听度的言语可懂度指数所解释的40%方差之外,又额外解释了40%的言语可懂度方差。
STM敏感度受损可能是由于分辨频谱峰值的能力下降以及利用TFS信息跟踪频谱峰值移动的能力下降共同导致的。将个体HI听众的STM敏感度估计值与听力阈值测量值相结合,比单独使用听力测量方法能更准确地预测言语可懂度。这些结果表明,基于STM的HI听众言语可懂度模型有很大的成功可能性。