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本文引用的文献

1
Use of a compound approach to derive auditory-filter-wide frequency-importance functions for vowels and consonants.使用复合方法推导元音和辅音的听觉滤波器宽频率重要性函数。
J Acoust Soc Am. 2012 Aug;132(2):1078-87. doi: 10.1121/1.4730905.
2
Relative contribution of off- and on-frequency spectral components of background noise to the masking of unprocessed and vocoded speech.背景噪声的离频和频域成分对未处理语音和语音编码掩蔽的相对贡献。
J Acoust Soc Am. 2010 Oct;128(4):2075-84. doi: 10.1121/1.3478845.
3
An alternative to the computational Speech Intelligibility Index estimates: direct measurement of rectangular passband intelligibilities.计算语音可懂度指数估计的另一种方法:直接测量矩形通带可懂度。
J Exp Psychol Hum Percept Perform. 2011 Feb;37(1):296-302. doi: 10.1037/a0020411.
4
On the number of auditory filter outputs needed to understand speech: further evidence for auditory channel independence.关于理解语音所需的听觉滤波器输出数量:听觉通道独立性的进一步证据。
Hear Res. 2009 Sep;255(1-2):99-108. doi: 10.1016/j.heares.2009.06.005. Epub 2009 Jun 16.
5
Longitudinal changes in speech recognition in older persons.老年人言语识别的纵向变化。
J Acoust Soc Am. 2008 Jan;123(1):462-75. doi: 10.1121/1.2817362.
6
Factors influencing glimpsing of speech in noise.影响噪声中言语感知的因素。
J Acoust Soc Am. 2007 Aug;122(2):1165-72. doi: 10.1121/1.2749454.
7
Spectral weighting strategies for sentences measured by a correlational method.通过相关方法测量句子的频谱加权策略。
J Acoust Soc Am. 2007 Jun;121(6):3827-36. doi: 10.1121/1.2722211.
8
Effect of spectral frequency range and separation on the perception of asynchronous speech.频谱频率范围和间隔对异步语音感知的影响。
J Acoust Soc Am. 2007 Mar;121(3):1691-700. doi: 10.1121/1.2427113.
9
Isolating the energetic component of speech-on-speech masking with ideal time-frequency segregation.利用理想的时频分离来分离语音对语音掩蔽中的能量成分。
J Acoust Soc Am. 2006 Dec;120(6):4007-18. doi: 10.1121/1.2363929.
10
A glimpsing model of speech perception in noise.一种噪声中语音感知的一瞥模型。
J Acoust Soc Am. 2006 Mar;119(3):1562-73. doi: 10.1121/1.2166600.

重新审视句子和单词的频段重要性。

Band importance for sentences and words reexamined.

机构信息

Department of Speech and Hearing Science, The Ohio State University, Columbus, Ohio 43210, USA.

出版信息

J Acoust Soc Am. 2013 Jan;133(1):463-73. doi: 10.1121/1.4770246.

DOI:10.1121/1.4770246
PMID:23297918
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3548885/
Abstract

Band-importance functions were created using the "compound" technique [Apoux and Healy, J. Acoust. Soc. Am. 132, 1078-1087 (2012)] that accounts for the multitude of synergistic and redundant interactions that take place among speech bands. Functions were created for standard recordings of the speech perception in noise (SPIN) sentences and the Central Institute for the Deaf (CID) W-22 words using 21 critical-band divisions and steep filtering to eliminate the influence of filter slopes. On a given trial, a band of interest was presented along with four other bands having spectral locations determined randomly on each trial. In corresponding trials, the band of interest was absent and only the four other bands were present. The importance of the band of interest was determined by the difference between paired band-present and band-absent trials. Because the locations of the other bands changed randomly from trial to trial, various interactions occurred between the band of interest and other speech bands which provided a general estimate of band importance. Obtained band-importance functions differed substantially from those currently available for identical speech recordings. In addition to differences in the overall shape of the functions, especially for the W-22 words, a complex microstructure was observed in which the importance of adjacent frequency bands often varied considerably. This microstructure may result in better predictive power of the current functions.

摘要

使用“复合”技术创建了带重要性函数[Apoux 和 Healy,J. Acoust. Soc. Am. 132, 1078-1087(2012)],该技术考虑了语音带之间发生的众多协同和冗余相互作用。使用 21 个临界频带划分和陡峭滤波来消除滤波器斜率的影响,为语音感知噪声(SPIN)句子和中央聋人研究所(CID)W-22 词的标准录音创建了函数。在给定的试验中,与四个其他具有随机确定的频谱位置的频带一起呈现感兴趣的频带。在相应的试验中,感兴趣的频带不存在,只有四个其他频带存在。通过比较配对的带通和带阻试验来确定感兴趣频带的重要性。由于其他频带的位置在每次试验中都是随机变化的,因此感兴趣频带与其他语音频带之间发生了各种相互作用,这提供了频带重要性的一般估计。获得的带重要性函数与当前用于相同语音记录的函数有很大不同。除了函数整体形状的差异外,特别是对于 W-22 单词,还观察到了复杂的微观结构,其中相邻频带的重要性经常有很大差异。这种微观结构可能会提高当前函数的预测能力。