High-roubustness keystroke recognition method based on acoustic spatial gradient

Ying LIU; Kangkang HAN; Zhihong QIAN

doi:10.11959/j.issn.1000-436x.2020095

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High-roubustness keystroke recognition method based on acoustic spatial gradient

Papers | 更新时间：2024-06-05

- High-roubustness keystroke recognition method based on acoustic spatial gradient
- Journal on Communications Vol. 41, Issue 5, Pages: 96-103(2020)
- 作者机构：
  
  1. 辽宁工程技术大学电子与信息工程学院，辽宁葫芦岛 125105
  2. 北京邮电大学电子工程学院，北京 100876
  3. 吉林大学通信工程学院，吉林长春 130022
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program of China(2018YFB1403300);The Project of Educational Commission of Liaoning Province(LJ2017QL013);Liaoning Province Doctor Startup Fund(20170520098);The Natural Science Foundation of Liaoning Province(2019-ZD-0038);The Project of Innovative Talents Support of Liaoning Province(LR2016045)
- DOI：10.11959/j.issn.1000-436x.2020095
  CLC： TP391
- Online First：2020-05，
  
  Published：25 May 2020
- 稿件说明：
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Ying LIU, Kangkang HAN, Zhihong QIAN. High-roubustness keystroke recognition method based on acoustic spatial gradient[J]. Journal on Communications, 2020, 41(5): 96-103.
DOI：

Ying LIU, Kangkang HAN, Zhihong QIAN. High-roubustness keystroke recognition method based on acoustic spatial gradient[J]. Journal on Communications, 2020, 41(5): 96-103. DOI： 10.11959/j.issn.1000-436x.2020095.

摘要

针对声音信号受实际环境噪声影响引起耳蜗倒谱系数（CFCC）波动是导致击键内容识别率低的主要原因，研究相邻键CFCC之间的空间特征，建立基于点的CFCC空间梯度结构；在此基础上，在训练集和测试上研究CFCC空间梯度对击键内容识别的影响及确切邻域的点选取；最后，建立基于声音的高稳健性击键内容识别方法。在不同环境下进行的实验表明，所提CFCC空间梯度声音特征效果较好，识别准确率为96.15% 。

Abstract

For the fluctuation of CFCC caused by environmental noise is the main reason for the low accuracy of keystroke detection

the spatial characteristics of adjacent between CFCC were studied

and the spatial gradient structure of CFCC based on points was established.On this basis

the effect of CFCC spatial gradient on keystroke content recognition and the selection of precise neighborhood points were studied on training and testing.Finally

a high-robustness keystroke recognition algorithm based on acoustic signals was constructed.Extensive experiments in different environments demonstrate that the proposed CFCC spatial gradient sound feature achieves great performance and the recognition accuracy is 96.15%.

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references

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