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Non-Uniform Microphone Arrays for Robust Speech Source Localization for Smartphone-Assisted Hearing Aid Devices

机译:非均匀麦克风阵列,用于智能手机辅助助听器的可靠语音源定位

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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.
机译:健壮的语音源本地化(SSL)是助听器(HAD)语音处理管道的重要组成部分。已知通过到达时间方向(TDOA)估计的SSL可以改善嘈杂环境中HAD的性能,从而为助听器用户提供更好的聆听体验。现在,智能手机具有通过有线或无线通道连接到HAD的功能。在本文中,我们介绍了有关非均匀非线性麦克风阵列(NUNLA)几何结构的发现,这些几何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。该方法是在基于帧的TDOA估计算法上实现的,该算法使用改进的基于字典的奇异值分解方法(SVD)来在非常低的信噪比(SNR)下定位单个语音源。与为统一麦克风阵列开发的大多数方法不同,该方法具有较低的空间混叠以及较低的空间模糊性,同时提供了具有360°DOA扫描功能的强大的低误差。我们介绍了不同类型的麦克风阵列之间的比较,并比较了所提出方法的性能。

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