Ganguly Anshuman, Panahi Issa
Department of Electrical Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
J Signal Process Syst. 2018 Oct;90(10):1415-1435. doi: 10.1007/s11265-017-1297-8. Epub 2017 Nov 9.
Robust speech source localization (SSL) is an important component of the speech processing pipeline for hearing aid devices (HADs). SSL via time direction of arrival (TDOA) estimation has been known to improve performance of HADs in noisy environments, thereby providing better listening experience for hearing aid users. Smartphones now possess the capability to connect to the HADs through wired or wireless channel. In this paper, we present our findings about the non-uniform non-linear microphone array (NUNLA) geometry for improving SSL for HADs using an L-shaped three-element microphone array available on modern smartphones. The proposed method is implemented on a frame-based TDOA estimation algorithm using a modified Dictionary-based singular value decomposition method (SVD) method for localizing single speech sources under very low signal to noise ratios (SNR). Unlike most methods developed for uniform microphone arrays, the proposed method has low spatial aliasing as well as low spatial ambiguity while providing a robust low-error with 360° DOA scanning capability. We present the comparison among different types of microphone arrays, as well as compare their performance using the proposed method.
鲁棒语音源定位（SSL）是助听器设备（HAD）语音处理流程的重要组成部分。通过到达时间（TDOA）估计实现的SSL已被证明可以提高HAD在嘈杂环境中的性能，从而为助听器用户提供更好的聆听体验。智能手机现在具备通过有线或无线通道连接到HAD的能力。在本文中，我们展示了关于非均匀非线性麦克风阵列（NUNLA）几何结构的研究结果，该结构使用现代智能手机上可用的L形三元素麦克风阵列来改善HAD的SSL。所提出的方法在基于帧的TDOA估计算法上实现，该算法使用一种改进的基于字典的奇异值分解（SVD）方法，用于在极低信噪比（SNR）下定位单个语音源。与大多数为均匀麦克风阵列开发的方法不同，所提出的方法具有低空间混叠以及低空间模糊性，同时提供具有360°方位角扫描能力的鲁棒低误差。我们展示了不同类型麦克风阵列之间的比较，并使用所提出的方法比较它们的性能。
