计算机工程

• 开发研究与工程应用 • 上一篇    

飞机驾驶舱噪声环境下的飞行员语音端点检测

诸心阳  a,黄丹  a,陆燕玉  b,傅山  b   

  1. (上海交通大学 a.航空航天学院; b.电子信息与电气工程学院,上海 200240)
  • 收稿日期:2016-12-09 出版日期:2018-01-15 发布日期:2018-01-15
  • 作者简介:诸心阳(1991—),女,硕士研究生,主研方向为语音信号处理;黄丹,副研究员、博士;陆燕玉,博士后;傅山,教授、博士。
  • 基金项目:
    国家自然科学基金(61305141)。

Pilot Speech Endpoint Detection in Aircraft Cockpit Noisy Environment

ZHU Xinyang  a,HUANG Dan  a,LU Yanyu  b,FU Shan  b   

  1. (a.School of Aeronautics and Astronautics; b.School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University,Shanghai 200240,China)
  • Received:2016-12-09 Online:2018-01-15 Published:2018-01-15

摘要: 为在飞行驾驶舱噪声环境下准确判定飞行员语音端点,提出一种鲁棒语音端点检测方法。使用最优改进对数谱幅度估计语音增强算法进行初步语音降噪,通过Teager能量算子进一步滤除残余噪声,并将降噪后语音短时能量与子带谱熵的比值作为双门限判决参数,检测飞行员语音起止点。实验结果表明,与基于能量参数或频谱熵参数的语音端点检测方法相比,该方法能有效提高检测正确率。

关键词: 驾驶舱人为因素, 语音端点检测, 最优改进对数谱幅度估计算法, Teager能量算子, 子带谱熵

Abstract: In aircraft cockpit noisy environment,it is hard to detect pilot speech endpoint.Aiming at this problem,a robust Speech Endpoint Detection(SED) method is proposed.The initial speech denoising is carried out by using Optimally Modified Log-Spectral Amplitude Estimator(OM-LSA) speech enhancement algorithm,and Teager Energy Operator(TEO) is used to further filter out the residual noise.Meanwhile,the ratio of the short-term energy of the speech to the spectral entropy of the sub-band is used as the parameter of the double-threshold decision,so as to detect the start and end point of the pilot speech.Experimental results show that,compared with the SED method based on energy parameter or spectral entropy parameter,the proposed method can improve the detection accuracy effectively.

Key words: cockpit human factor, Speech Endpoint Detection(SED), Optimally Modified Log-Spectral Amplitude Estimator(OM-LSA) algorithm, Teager Energy Operator(TEO), sub-band spectral entropy

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