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首页> 外文期刊>Hearing Research: An International Journal >On the number of auditory filter outputs needed to understand speech: further evidence for auditory channel independence.
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On the number of auditory filter outputs needed to understand speech: further evidence for auditory channel independence.

机译:关于理解语音所需的听觉过滤器输出的数量:关于听觉通道独立性的进一步证据。

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The number of auditory filter outputs required to identify phonemes was estimated in two experiments. Stimuli were divided into 30 contiguous equivalent rectangular bandwidths (ERB(N)) spanning 80-7563Hz. Normal-hearing listeners were presented with limited numbers of bands having frequency locations determined randomly from trial to trial to provide a general view, i.e., irrespective of specific band location, of the number of 1-ERB(N)-wide speech bands needed to identify phonemes. The first experiment demonstrated that 20 such bands are required to accurately identify vowels, and 16 are required to identify consonants. In the second experiment, speech-shaped noise or time-reversed speech was introduced to the non-speech bands at various signal-to-noise ratios. Considerably elevated noise levels were necessary to substantially affect phoneme recognition, confirming a high degree of channel independence in the auditory system. The independence observed between auditory filter outputs supports current views of speech recognition in noise in which listeners extract and combine pieces of information randomly distributed both in time and frequency. These findings also suggest that the ability to partition incoming sounds into a large number of narrow bands, an ability often lost in cases of hearing impairment or cochlear implantation, is critical for speech recognition in noise.
机译:在两个实验中估计了识别音素所需的听觉过滤器输出的数量。刺激被分为30个连续的等效矩形带宽(ERB(N)),跨度为80-7563Hz。向正常听觉的听众提供了有限数量的频段,这些频段的频率位置在每次试验之间都是随机确定的,以提供一个总体视图,即不考虑特定的频段位置,即需要多少个1-ERB(N)宽语音频段。识别音素。第一个实验表明,需要20个这样的频段才能准确识别元音,而需要16个频段才能识别辅音。在第二个实验中,以各种信噪比将语音形噪声或时间反转语音引入了非语音频带。要显着影响音素识别,必须提高噪声水平,从而确认听觉系统中通道的高度独立性。听觉滤波器输出之间观察到的独立性支持当前在语音中识别语音的观点,其中听众提取并组合在时间和频率上随机分布的信息。这些发现还表明,将进入的声音划分为大量窄带的能力(在听力障碍或耳蜗植入的情况下经常丧失的能力)对于噪声中的语音识别至关重要。

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