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人工耳蜗 n-of-m 策略对噪声干扰言语识别时的信噪比的影响。

Effect of cochlear implant n-of-m strategy on signal-to-noise ratio below which noise hinders speech recognition.

机构信息

Amsterdam UMC, Vrije Universiteit Amsterdam, Otolaryngology-Head and Neck Surgery, Ear and Hearing, Amsterdam Public Health Research Institute, De Boelelaan 1117, Amsterdam,

出版信息

J Acoust Soc Am. 2019 May;145(5):EL417. doi: 10.1121/1.5107430.

Abstract

Speech recognition was measured in 24 normal-hearing subjects for unprocessed speech and for speech processed by a cochlear implant Advanced Combination Encoder (ACE) coding strategy in quiet and at various signal-to noise ratios (SNRs). All signals were low- or high-pass filtered to avoid ceiling effects. Surprisingly, speech recognition performance plateaus at approximately 22 dB SNR for both speech types, implying that ACE processing has no effect on the upper limit of the effective SNR range. Speech recognition improved significantly above 15 dB SNR, suggesting that the upper limit used in the Speech Intelligibility Index should be reconsidered.

摘要

在安静环境中和不同信噪比下,对 24 名正常听力受试者的未处理语音和经过 Cochlear 植入物高级组合编码器 (ACE) 编码策略处理的语音进行语音识别测试。所有信号都经过低通或高通滤波,以避免天花板效应。令人惊讶的是,对于这两种语音类型,语音识别性能在大约 22dB SNR 时趋于平稳,这意味着 ACE 处理对有效 SNR 范围的上限没有影响。在 SNR 高于 15dB 时,语音识别性能显著提高,这表明语音可懂度指数中使用的上限值应重新考虑。

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