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首页> 外文期刊>Journal of the American Academy of Audiology >Speech Understanding and Sound Source Localization by Cochlear Implant Listeners Using a Pinna-Effect Imitating Microphone and an Adaptive Beamformer
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Speech Understanding and Sound Source Localization by Cochlear Implant Listeners Using a Pinna-Effect Imitating Microphone and an Adaptive Beamformer

机译:使用PINNA效应模仿麦克风和自适应波束形成器的Cochlear植入听众的语音理解和声源定位

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摘要

Background:Sentence understanding scores for patients with cochlear implants (CIs) when tested in quiet are relatively high. However, sentence understanding scores for patients with CIs plummet with the addition of noise.Purpose:To assess, for patientswith CIs (MED-EL), (1) the value to speech understanding of two new, noise-reducing microphone settings and (2) the effect of the microphone settings on sound source localization.Research Design:Single-subject, repeated measures design. For tests of speech understanding,repeated measures on (1) number of CIs (one, two), (2) microphone type (omni, natural, adaptive beamformer), and (3) type of noise (restaurant, cocktail party). For sound source localization, repeated measures on type of signal (low-pass [LP], high-pass [HP], broadband noise).StudySample:Ten listeners, ranging in age from 48 to 83 yr (mean = 57 yr), participated in this prospective study.Intervention:Speech understanding was assessed in two noise environments using monaural and bilateral CIs fit with three microphone types. Sound source localizationwas assessed using three microphone types.Data Collection and Analysis:In Experiment 1, sentence understanding scores (in terms of percent words correct) were obtained in quiet and in noise. For each patient, noise was first added to the signal to drive performance off ofthe ceiling in the bilateral CI-omni microphone condition. The other conditions were then administered at that signal-to-noise ratio in quasi-random order. In Experiment 2, sound source localization accuracy was assessed for three signal types using a 13-loudspeaker array over a 180° arc.The dependent measure was root-mean-score error.Results:Both the natural and adaptive microphone settings significantly improved speech understanding in the two noise environments. The magnitude of the improvement varied between 16 and 19 percentage points for tests conductedin the restaurant environment and between 19 and 36 percentage points for tests conducted in the cocktail party environment. In the restaurant and cocktail party environments, both the natural and adaptive settings, when implemented on a single CI, allowed scores that were as good as, or better,than scores in the bilateral omni test condition. Sound source localization accuracy was unaltered by either the natural or adaptive settings for LP, HP, or wideband noise stimuli.Conclusion:The data support the use of the natural microphone setting as a default setting.The natural setting (1) provides better speech understanding in noise than the omni setting, (2) does not impair sound source localization, and (3) retains low-frequency sensitivity to signals from the rear. Moreover, bilateral CIs equipped with adaptive beamforming technology can engenderspeech understanding scores in noise that fall only a little short of scores for a single CI in quiet.
机译:背景:在安静测试时,句子了解耳蜗植入物(CIS)的分数比较高。但是,通过添加噪声的CIS下降患者的句子理解分数。对于CIS(MED-EL)进行评估,为患者进行评估,(1)对两个新的,降噪麦克风设置的语音理解的价值(2 )麦克风设置对声源定位的效果。搜索设计:单个主题,重复测量设计。对于语音理解的测试,重复措施(1)CIS(一,二),(2)麦克风型(OMNI,天然,自适应波束形成器)和(3)噪声类型(餐厅,鸡尾酒会)。对于声源定位,对信号类型的重复措施(低通[LP],高通[HP],宽带噪声).sudysample:10个听众,年龄从48到83 YR(平均= 57 YR),参与了这项潜在的研究。注意:使用单声道和双边CIS适合三种麦克风类型,在两个噪声环境中评估语音理解。使用三种麦克风类型评估声源定位.DATA收集和分析:在实验1中,在安静和噪声中获得了解得分(以百分比正确的单词)。对于每位患者,首先将噪声添加到信号中以驱动双边CI-OMNI麦克风条件下的天花板的性能。然后以准随机顺序以该信噪比给予其他条件。在实验2中,使用13扬声器阵列在180°弧上使用13扬声器阵列进行三个信号类型的声源定位精度。依赖性措施是根均衡错误。结果:自然和自适应麦克风设置都显着改善了语音理解在两个噪声环境中。测试的改善程度在餐厅环境中进行了16至19个百分点,在鸡尾酒会环境中进行的测试进行了19至36个百分点。在餐厅和鸡尾酒会环境中,自然和自适应设置都在单个CI上实现时,允许分数与双边全部测试条件中的分数一样好或更好。 LP,HP或宽带噪声刺激的自然或自适应设置,声源定位精度未替换.Conclusion:数据支持使用自然麦克风设置作为默认设置。自然设置(1)提供更好的语音理解在噪声中,而不是Omni设置,(2)不损害声源定位,(3)保留从后部的信号的低频灵敏度。此外,配备自适应波束形成技术的双边CIS可以在安静的单一CI中占据噪音中的噪音中的分数。

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