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NAPLIB:用于实时和离线神经声学处理的开源工具箱。

NAPLIB: AN OPEN SOURCE TOOLBOX FOR REAL-TIME AND OFFLINE NEURAL ACOUSTIC PROCESSING.

作者信息

Khalighinejad Bahar, Nagamine Tasha, Mehta Ashesh, Mesgarani Nima

机构信息

Department of Electrical Engineering, Columbia University, New York, USA.

Department of Neurosurgery, Hofstra Northwell School of Medicine and Feinstein Institute for Medical Research, Manhasset, New York, USA.

出版信息

Proc IEEE Int Conf Acoust Speech Signal Process. 2017 Mar;2017:846-850. doi: 10.1109/ICASSP.2017.7952275. Epub 2017 Jun 19.

Abstract

In this paper, we introduce the Neural Acoustic Processing Library (NAPLib), a toolbox containing novel processing methods for real-time and offline analysis of neural activity in response to speech. Our method divides the speech signal and resultant neural activity into segmental units (e.g., phonemes), allowing for fast and efficient computations that can be implemented in real-time. NAPLib contains a suite of tools that characterize various properties of the neural representation of speech, which can be used for functionality such as characterizing electrode tuning properties, brain mapping and brain computer interfaces. The library is general and applicable to both invasive and non-invasive recordings, including electroencephalography (EEG), electrocorticography (ECoG) and magnetoecnephalography (MEG). In this work, we describe the structure of NAPLib, as well as demonstrating its use in both EEG and ECoG. We believe NAPLib provides a valuable tool to both clinicians and researchers who are interested in the representation of speech in the brain.

摘要

在本文中,我们介绍了神经声学处理库(NAPLib),这是一个工具箱,包含用于实时和离线分析响应语音的神经活动的新颖处理方法。我们的方法将语音信号和由此产生的神经活动划分为分段单元(例如音素),从而实现可以实时实施的快速高效计算。NAPLib包含一套工具,用于表征语音神经表征的各种属性,可用于诸如表征电极调谐属性、脑图谱绘制和脑机接口等功能。该库具有通用性,适用于侵入性和非侵入性记录,包括脑电图(EEG)、皮层脑电图(ECoG)和脑磁图(MEG)。在这项工作中,我们描述了NAPLib的结构,并展示了其在EEG和ECoG中的应用。我们相信,NAPLib为对大脑中语音表征感兴趣的临床医生和研究人员提供了一个有价值的工具。

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NAPLIB: AN OPEN SOURCE TOOLBOX FOR REAL-TIME AND OFFLINE NEURAL ACOUSTIC PROCESSING.NAPLIB:用于实时和离线神经声学处理的开源工具箱。
Proc IEEE Int Conf Acoust Speech Signal Process. 2017 Mar;2017:846-850. doi: 10.1109/ICASSP.2017.7952275. Epub 2017 Jun 19.

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