Tokgöz Serkan, Kovalyov Anton, Panahi Issa
Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX.
IEEE Workshop Signal Process Syst. 2020 Oct;2020. doi: 10.1109/sips50750.2020.9195217. Epub 2020 Sep 23.
In this paper, we present a real-time noise-robust direction of arrival (DOA) estimation technique using only the three built-in microphones of the modern Android-based smartphone. The proposed method eliminates the 'front-back' ambiguity caused by the symmetry of the two microphones reported previously and improves the performance of DOA estimation in noisy speech environments. Our method enhances the spatial awareness of hearing-impaired users by displaying the precise DOA angle of speech source on their smartphone screen. For increased efficiency, noise-robustness, and accuracy of the proposed DOA estimation method, a spectral pre-filtering technique and a Voice Activity Detector (VAD) based post-filtering are used along with a modified generalized cross-correlation (GCC) technique. Real recorded and simulated data under realistic noisy conditions are used in the evaluations of the proposed algorithm. Real-time implementation of the proposed system is carried out on an Android-based smartphone without any additional hardware or external microphone attachments. Experimental results show the performance of the proposed method versus those without pre or post-filtering under three different noisy conditions with 0dB to 10dB signal to noise ratios (SNRs).
在本文中，我们提出了一种仅使用现代安卓智能手机的三个内置麦克风的实时抗噪到达方向（DOA）估计技术。所提出的方法消除了先前报道的由两个麦克风的对称性引起的“前后”模糊性，并提高了在嘈杂语音环境中DOA估计的性能。我们的方法通过在听力受损用户的智能手机屏幕上显示语音源的精确DOA角度，增强了他们的空间感知能力。为了提高所提出的DOA估计方法的效率、抗噪性和准确性，采用了一种频谱预滤波技术和基于语音活动检测器（VAD）的后滤波，以及一种改进的广义互相关（GCC）技术。在所提出算法的评估中使用了在实际噪声条件下的真实录制和模拟数据。所提出系统的实时实现是在基于安卓的智能手机上进行的，无需任何额外硬件或外部麦克风附件。实验结果展示了所提出方法在0dB至10dB信噪比（SNR）的三种不同噪声条件下相对于未进行预滤波或后滤波方法的性能。
