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首页> 外文期刊>Journal of the Association for Research in Otolaryngology >Tone-in-Noise Detection Using Envelope Cues: Comparison of Signal-Processing-Based and Physiological Models
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Tone-in-Noise Detection Using Envelope Cues: Comparison of Signal-Processing-Based and Physiological Models

机译:使用包络线索进行音中噪声检测:基于信号处理和生理模型的比较

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Tone-in-noise detection tasks with reproducible noise maskers have been used to identify cues that listeners use to detect signals in noisy environments. Previous studies have shown that energy, envelope, and fine-structure cues are significantly correlated to listeners’ performance for detection of a 500-Hz tone in noise. In this study, envelope cues were examined for both diotic and dichotic tone-in-noise detection using both stimulus-based signal processing and physiological models. For stimulus-based envelope cues, a modified envelope slope model was used for the diotic condition and the binaural slope of the interaural envelope difference model for the dichotic condition. Stimulus-based models do not include key nonlinear transformations in the auditory periphery such as compression, rate and dynamic range adaptation, and rate saturation, all of which affect the encoding of the stimulus envelope. For physiological envelope cues, stimuli were passed through models for the auditory nerve (AN), cochlear nucleus, and inferior colliculus (IC). The AN and cochlear nucleus models included appropriate modulation gain, another transformation of the stimulus envelope that is not typically included in stimulus-based models. A model IC cell was simulated with a linear band-pass modulation filter. The average discharge rate and response fluctuations of the model IC cell were compared to human performance. Previous studies have predicted a significant amount of the variance across reproducible noise maskers in listeners’ detection using stimulus-based envelope cues. In this study, a physiological model that includes neural mechanisms that affect encoding of the stimulus envelope predicts a similar amount of the variance in listeners’ performance across noise maskers.
机译:具有可重现的噪声掩蔽器的音中噪声检测任务已被用来识别听众用来在嘈杂环境中检测信号的线索。先前的研究表明,能量,包络和精细结构的提示与侦听器在检测500 Hz音调时的表现密切相关。在这项研究中,使用基于刺激的信号处理和生理模型,对包膜提示进行了二重和二重噪声检测。对于基于刺激的包络提示,将改良的包络斜率模型用于双歧性条件,而将双耳包络差异模型的双耳斜率用于双歧性条件。基于刺激的模型在听觉外围不包括关键的非线性变换,例如压缩,速率和动态范围自适应以及速率饱和,所有这些都会影响刺激包络的编码。对于生理性包膜信号,刺激通过听神经(AN),耳蜗核和下丘脑(IC)的模型传递。 AN和耳蜗核模型包括适当的调制增益,这是刺激包络的另一种转换,通常不包含在基于刺激的模型中。使用线性带通调制滤波器对模型IC单元进行了仿真。将模型IC电池的平均放电率和响应波动与人类表现进行了比较。先前的研究预测,在使用基于刺激的包络提示进行侦听的听众中,可重现的噪声掩蔽器之间的差异很大。在这项研究中,一个生理模型包括影响刺激包络编码的神经机制,可以预测听众在整个噪声掩蔽者的表现中出现相似程度的差异。

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