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用于理解声码句子的承载信息的声学变化的频谱和时间分辨率。

Spectral and temporal resolutions of information-bearing acoustic changes for understanding vocoded sentences.

作者信息

Stilp Christian E, Goupell Matthew J

机构信息

Department of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky 40292.

Department of Hearing and Speech Sciences, University of Maryland, College Park, Maryland 20742.

出版信息

J Acoust Soc Am. 2015 Feb;137(2):844-55. doi: 10.1121/1.4906179.

Abstract

Short-time spectral changes in the speech signal are important for understanding noise-vocoded sentences. These information-bearing acoustic changes, measured using cochlea-scaled entropy in cochlear implant simulations [CSECI; Stilp et al. (2013). J. Acoust. Soc. Am. 133(2), EL136-EL141; Stilp (2014). J. Acoust. Soc. Am. 135(3), 1518-1529], may offer better understanding of speech perception by cochlear implant (CI) users. However, perceptual importance of CSECI for normal-hearing listeners was tested at only one spectral resolution and one temporal resolution, limiting generalizability of results to CI users. Here, experiments investigated the importance of these informational changes for understanding noise-vocoded sentences at different spectral resolutions (4-24 spectral channels; Experiment 1), temporal resolutions (4-64 Hz cutoff for low-pass filters that extracted amplitude envelopes; Experiment 2), or when both parameters varied (6-12 channels, 8-32 Hz; Experiment 3). Sentence intelligibility was reduced more by replacing high-CSECI intervals with noise than replacing low-CSECI intervals, but only when sentences had sufficient spectral and/or temporal resolution. High-CSECI intervals were more important for speech understanding as spectral resolution worsened and temporal resolution improved. Trade-offs between CSECI and intermediate spectral and temporal resolutions were minimal. These results suggest that signal processing strategies that emphasize information-bearing acoustic changes in speech may improve speech perception for CI users.

摘要

语音信号中的短时频谱变化对于理解噪声编码句子很重要。这些携带信息的声学变化,在人工耳蜗模拟中使用耳蜗尺度熵进行测量[耳蜗尺度熵(CSECI);斯蒂尔普等人(2013年)。《美国声学学会杂志》133(2),EL136 - EL141;斯蒂尔普(2014年)。《美国声学学会杂志》135(3),1518 - 1529],可能有助于更好地理解人工耳蜗(CI)使用者的言语感知。然而,仅在一种频谱分辨率和一种时间分辨率下测试了CSECI对正常听力听众的感知重要性,这限制了结果对CI使用者的普遍适用性。在此,实验研究了这些信息变化对于在不同频谱分辨率(4 - 24个频谱通道;实验1)、时间分辨率(用于提取幅度包络的低通滤波器的截止频率为4 - 64 Hz;实验2)或当两个参数都变化时(6 - 12个通道,8 - 32 Hz;实验3)理解噪声编码句子的重要性。用噪声替换高CSECI区间比替换低CSECI区间更能降低句子清晰度,但这仅在句子具有足够的频谱和/或时间分辨率时才成立。随着频谱分辨率变差和时间分辨率提高,高CSECI区间对言语理解更为重要。CSECI与中等频谱和时间分辨率之间的权衡最小。这些结果表明,强调语音中携带信息的声学变化的信号处理策略可能会改善CI使用者的言语感知。

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