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首页> 外文期刊>The Journal of the Acoustical Society of America >Predicting the effect of hearing loss and audibility on amplified speech reception in a multi-talker listening scenario
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Predicting the effect of hearing loss and audibility on amplified speech reception in a multi-talker listening scenario

机译:预测多说话者收听情况下听力损失和可听性对放大语音接收的影响

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Auditive and cognitive influences on speech perception in a complex situation were investigated in listeners with normal hearing (NH) and hearing loss (HL). The speech corpus used was the Nonsense-Syllable Response Measure [NSRM; Woods and Kalluri, (2010). International Hearing Aid Research Conference, pp. 40-41], a 12-talker corpus which combines 154 nonsense syllables with 8 different carrier phrases. Listeners heard NSRM sentences in quiet, background noise, and in background noise plus other "jammer" NSRM sentences. All stimuli were linearly amplified. A "proficiency" value, determined from the results in quiet and the quiet-condition speech intelligibility index (SII), was used with the SII in predicting results in the other conditions. Results for nine of ten NH subjects were well-predicted (within the limits of binomial variability) in the noise condition, as were eight of these subjects in the noise-plus-jammers condition. All 16 HL results were well-predicted in the noise condition, as were 9 of the HL in the noise-plus-jammers condition. Hierarchical regression partialling out the effects of age found proficiency in noise-plus-jammers significantly correlated with results of "trail- making" tests, thought to index processing speed and attention-deployment ability, and proficiency in quiet and noise was found significantly correlated with results from a backward digit-span memory test.
机译:在听力正常(NH)和听力下降(HL)的听众中,研究了在复杂情况下听觉和认知对言语感知的影响。所使用的语音语料库是无意义音节响应量度[NSRM;伍兹和卡卢里(2010)。 [国际助听研究会议,第40-41页],是一个由12位说话者组成的语料库,它将154个无意义的音节与8个不同的载体短语组合在一起。听众听到了安静,背景噪音,背景噪音以及其他“干扰” NSRM句子中的NSRM句子。所有刺激线性扩增。根据安静和安静条件下语音清晰度指数(SII)的结果确定的“熟练度”值与SII一起用于预测其他条件下的结果。在噪声条件下,十个NH受试者中有九个的结果得到了很好的预测(在二项式变异性的范围内),在噪声加干扰条件下,这些受试者中的八个也得到了很好的预测。在噪声条件下,所有16个HL结果均得到了很好的预测,在噪声加干扰条件下,有9个HL结果也得到了很好的预测。分层回归分析了年龄的影响,发现噪声加干扰的熟练程度与“跟踪”测试的结果显着相关,认为索引处理速度和注意力部署能力​​与安静和噪音的熟练程度显着相关向后数字跨度内存测试的结果。

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