Clinical Evaluation of Signal-to-Noise Ratio-Based Noise Reduction in Nucleus® Cochlear Implant Recipients
Clinical Evaluation of Signal-to-Noise Ratio-Based Noise Reduction in Nucleus® Cochlear Implant Recipients
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DOI：
10.1097/aud.0b013e318201c200
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发表时间：
2011-05-01
期刊：
影响因子：
3.7
通讯作者：
Hersbach, Adam A.
中科院分区：
文献类型：
--
作者：
Dawson, Pam W.;Mauger, Stefan J.;Hersbach, Adam A.
目的：本研究的目的是调查实时降噪算法是否为实验室中的Cochiar（TM）Nucleus（R）人工耳蜗植入者提供语音感知益处。设计：降噪算法衰减掩蔽占主导地位的通道。它使用递归最小统计方法从单个麦克风输入在短期基础上估计每个通道的信噪比。在本临床评价中，该算法在两个程序（降噪程序1 [NR 1]和2 [NR 2]）中实现，这两个程序的降噪水平不同。这些程序使用先进的组合编码器（ACE T）的通道选择，并与ACE无降噪在13个经验丰富的人工耳蜗受试者进行了比较。自适应语音接收阈值（SRT）测试提供了三种不同类型的噪声：语音加权，鸡尾酒会，和街边的城市noise.Results的信噪比为50%的句子可懂度：在所有三种噪声类型，平均SRT为NR程序显着优于ACE。最大的改善发生在语音加权噪声上; NR 1和NR 2的SRT相对于ACE的获益分别为1.77 dB和2.14 dB。两个NR程序之间的言语感知得分没有显着差异。受试者报告没有退化的声音质量与实验programmes.Conclusions：降噪算法是成功的提高句子感知语音加权噪声，以及在更动态类型的背景噪声。该算法目前正在耳后处理器中进行试验，以便带回家使用。
Objective: The aim of this study was to investigate whether a real-time noise reduction algorithm provided speech perception benefit for Cochlear (TM) Nucleus (R) cochlear implant recipients in the laboratory.Design: The noise reduction algorithm attenuated masker-dominated channels. It estimated the signal-to-noise ratio of each channel on a short-term basis from a single microphone input, using a recursive minimum statistics method. In this clinical evaluation, the algorithm was implemented in two programs (noise reduction programs 1 [NR1] and 2 [NR2]), which differed in their level of noise reduction. These programs used advanced combination encoder (ACE T) channel selection and were compared with ACE without noise reduction in 13 experienced cochlear implant subjects. An adaptive speech reception threshold (SRT) test provided the signal-to-noise ratio for 50% sentence intelligibility in three different types of noises: speech-weighted, cocktail party, and street-side city noise.Results: In all three noise types, mean SRTs for both NR programs were significantly better than those for ACE. The greatest improvement occurred for speech-weighted noise; the SRT benefit over ACE was 1.77 dB for NR1 and 2.14 dB for NR2. There were no significant differences in speech perception scores between the two NR programs. Subjects reported no degradation in sound quality with the experimental programs.Conclusions: The noise reduction algorithm was successful in improving sentence perception in speech-weighted noise, as well as in more dynamic types of background noise. The algorithm is currently being trialed in a behind-the-ear processor for take-home use.