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The Contribution of Cognitive Factors to Individual Differences in Understanding Noise-Vocoded Speech in Young and Older Adults

机译:认知因素对理解年轻人和老年人语音中语音语音的个体差异的贡献

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Noise-vocoded speech is commonly used to simulate the sensation after cochlear implantation as it consists of spectrally degraded speech. High individual variability exists in learning to understand both noise-vocoded speech and speech perceived through a cochlear implant (CI). This variability is partly ascribed to differing cognitive abilities like working memory, verbal skills or attention. Although clinically highly relevant, up to now, no consensus has been achieved about which cognitive factors exactly predict the intelligibility of speech in noise-vocoded situations in healthy subjects or in patients after cochlear implantation. We aimed to establish a test battery that can be used to predict speech understanding in patients prior to receiving a CI. Young and old healthy listeners completed a noise-vocoded speech test in addition to cognitive tests tapping on verbal memory, working memory, lexicon and retrieval skills as well as cognitive flexibility and attention. Partial-least-squares analysis revealed that six variables were important to significantly predict vocoded-speech performance. These were the ability to perceive visually degraded speech tested by the Text Reception Threshold, vocabulary size assessed with the Multiple Choice Word Test, working memory gauged with the Operation Span Test, verbal learning and recall of the Verbal Learning and Retention Test and task switching abilities tested by the Comprehensive Trail-Making Test. Thus, these cognitive abilities explain individual differences in noise-vocoded speech understanding and should be considered when aiming to predict hearing-aid outcome.
机译:噪声语音编码语音通常用于模拟人工耳蜗植入后的感觉,因为它由频谱退化的语音组成。在学习理解噪声编码语音和通过人工耳蜗(CI)感知的语音时,存在很高的个体差异性。这种差异部分归因于不同的认知能力,例如工作记忆,语言技能或注意力。尽管在临床上高度相关,但到目前为止,在健康受试者或人工耳蜗植入后的患者中,哪些认知因素准确预测了语音编码情况下的语音清晰度尚无共识。我们旨在建立一个测试电池,可用来预测接受CI之前患者的语音理解。青年和老年人健康的听众除了通过对语言记忆,工作记忆,词汇和检索技巧以及认知灵活性和注意力的认知测试之外,还完成了噪声编码语音测试。偏最小二乘分析表明,六个变量对于显着预测声码语音性能很重要。这些功能包括:感知通过文本接收阈值测试的视觉退化语音的能力,通过多项选择单词测试评估的词汇量,通过操作范围测试衡量的工作记忆,口头学习和口头学习与保留测试的回忆以及任务切换能力经综合试行测试。因此,这些认知能力可以解释语音语音理解中的个体差异,因此在预测助听结果时应予以考虑。

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