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应用音高感知模型研究刺激场扩展对人工耳蜗植入者音高排序能力的影响。

Application of a pitch perception model to investigate the effect of stimulation field spread on the pitch ranking abilities of cochlear implant recipients.

作者信息

Erfanian Saeedi Nafise, Blamey Peter J, Burkitt Anthony N, Grayden David B

机构信息

NeuroEngineering Laboratory, Dept. of Electrical & Electronic Engineering, University of Melbourne, Australia; Centre for Neural Engineering, University of Melbourne, Australia.

The Bionics Institute, East Melbourne, Australia; Dept. of Medical Bionics, University of Melbourne, Australia.

出版信息

Hear Res. 2014 Oct;316:129-37. doi: 10.1016/j.heares.2014.08.006. Epub 2014 Sep 2.

DOI:10.1016/j.heares.2014.08.006
PMID:25193552
Abstract

Although many cochlear implant (CI) recipients perceive speech very well in favorable conditions, they still have difficulty with music, speech in noisy environments, and tonal languages. Studies show that CI users' performance in these tasks are correlated with their ability to perceive pitch. The spread of stimulation field from the electrodes to the auditory nerve is one of the factors affecting performance. This study proposes a model of auditory perception to predict the performance of CI users in pitch ranking tasks using an existing sound processing scheme. The model is then used as a platform to investigate the effect of stimulation field spread on performance.

摘要

尽管许多人工耳蜗(CI)接受者在良好条件下能很好地感知语音,但他们在音乐、嘈杂环境中的语音以及声调语言方面仍存在困难。研究表明,CI使用者在这些任务中的表现与他们感知音高的能力相关。从电极到听神经的刺激场扩散是影响表现的因素之一。本研究提出了一种听觉感知模型,以使用现有的声音处理方案预测CI使用者在音高排序任务中的表现。然后将该模型用作一个平台,来研究刺激场扩散对表现的影响。

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引用本文的文献

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Estimating Pitch Information From Simulated Cochlear Implant Signals With Deep Neural Networks.基于深度神经网络的人工耳蜗模拟信号基频信息估计
Trends Hear. 2024 Jan-Dec;28:23312165241298606. doi: 10.1177/23312165241298606.
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Unifying information theory and machine learning in a model of electrode discrimination in cochlear implants.将信息论和机器学习在耳蜗植入电极判别模型中统一起来。
PLoS One. 2021 Sep 20;16(9):e0257568. doi: 10.1371/journal.pone.0257568. eCollection 2021.
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Learning Pitch with STDP: A Computational Model of Place and Temporal Pitch Perception Using Spiking Neural Networks.
基于STDP学习音高:一种使用脉冲神经网络的位置和时间音高感知计算模型。
PLoS Comput Biol. 2016 Apr 6;12(4):e1004860. doi: 10.1371/journal.pcbi.1004860. eCollection 2016 Apr.