Effects of spectral smearing on performance of the spectral ripple and spectro-temporal ripple tests

Effects of spectral smearing on performance of the spectral ripple and spectro-temporal ripple tests
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DOI:
10.1121/1.4971419
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发表时间:
2016-12-01
影响因子:
2.4
通讯作者:
Moore, Brian C. J.
Moore, Brian C. J.
中科院分区:
物理与天体物理3区
文献类型:
--
作者:
Narne, Vijaya Kumar;Sharma, Mridula;Moore, Brian C. J.

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本研究的主要目的是使用光谱涂抹来评估使用静止声音的光谱纹波测试 (SRt) 和最近的滑动纹波变体(称为光谱时间纹波测试 (STRt))在测量降低的光谱分辨率方面的功效。在实验 1 中,使用四种光谱涂抹量(未涂抹、轻度、中度和严重)测量最高可检测波纹密度。阈值随着涂抹的增加而恶化,并且在三种涂抹条件下,SRt 和 STRt 的阈值相似。对于未涂抹的刺激,STRt 的阈值明显高于(更好)于 SRt 的阈值。模拟(伽玛通)听觉滤波器输出的振幅波动以 6400 Hz 以上为中心,被认为为 STRt 刺激提供了潜在的检测线索。实验 2 使用能量低于和高于 SRt 和 STRt 刺激通带的陷波噪声来减少 STRt 中的混杂线索。对于未涂抹和涂抹的刺激,STRt 和 SRt 的阈值几乎相同,表明 STRt 的混杂线索已被缺口噪声消除。使用激励模式模型可以相当准确地预测存在缺口噪声时获得的阈值。 (C) 2016 年美国声学学会。
The main aim of this study was to use spectral smearing to evaluate the efficacy of a spectral ripple test (SRt) using stationary sounds and a recent variant with gliding ripples called the spectrotemporal ripple test (STRt) in measuring reduced spectral resolution. In experiment 1 the highest detectable ripple density was measured using four amounts of spectral smearing (unsmeared, mild, moderate, and severe). The thresholds worsened with increasing smearing and were similar for the SRt and the STRt across the three conditions with smearing. For unsmeared stimuli, thresholds were significantly higher (better) for the STRt than for the SRt. An amplitude fluctuation at the outputs of simulated (gammatone) auditory filters centered above 6400 Hz was identified as providing a potential detection cue for the STRt stimuli. Experiment 2 used notched noise with energy below and above the passband of the SRt and STRt stimuli to reduce confounding cues in the STRt. Thresholds were almost identical for the STRt and SRt for both unsmeared and smeared stimuli, indicating that the confounding cue for the STRt was eliminated by the notched noise. Thresholds obtained with notched noise present could be predicted reasonably accurately using an excitation-pattern model. (C) 2016 Acoustical Society of America.