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A Diagonal-Steering-Based Binaural Beamforming Algorithm Incorporating a Diagonal Speech Localizer for Persons With Bilateral Hearing Impairment

机译：一种基于对角转向的双耳波束成形算法，该算法结合了对角听力障碍者的对角语音定位器

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摘要

Previously suggested diagonal-steering algorithms for binaural hearing support devices have commonly assumed that the direction of the speech signal is known in advance, which is not always the case in many real circumstances. In this study, a new diagonal-steering-based binaural speech localization (BSL) algorithm is proposed, and the performances of the BSL algorithm and the binaural beamforming algorithm, which integrates the BSL and diagonal-steering algorithms, were evaluated using actual speech-in-noise signals in several simulated listening scenarios. Testing sounds were recorded in a KEMAR mannequin setup and two objective indices, improvements in signal-to-noise ratio (SNRi) and segmental SNR (segSNR(i)), were utilized for performance evaluation. Experimental results demonstrated that the accuracy of the BSL was in the 90-100% range when input SNR was -10 to +5dB range. The average differences between the -adjusted and -fixed diagonal-steering algorithms (for -15 to +5dB input SNR) in the talking in the restaurant scenario were 0.203-0.937dB for SNRi and 0.052-0.437dB for segSNR(i), and in the listening while car driving scenario, the differences were 0.387-0.835dB for SNRi and 0.259-1.175dB for segSNR(i). In addition, the average difference between the BSL-turned-on and the BSL-turned-off cases for the binaural beamforming algorithm in the listening while car driving scenario was 1.631-4.246dB for SNRi and 0.574-2.784dB for segSNR(i). In all testing conditions, the -adjusted diagonal-steering and BSL algorithm improved the values of the indices more than the conventional algorithms. The binaural beamforming algorithm, which integrates the proposed BSL and diagonal-steering algorithm, is expected to improve the performance of the binaural hearing support devices in noisy situations.
机译：先前提出的用于双耳助听器的对角转向算法通常假定语音信号的方向是事先已知的，在许多实际情况下并不总是这样。在这项研究中，提出了一种新的基于对角线导向的双耳语音定位（BSL）算法，并使用实际语音对BSL算法和将BSL和对角线导向算法相结合的双耳波束形成算法的性能进行了评估，几种模拟收听场景中的噪声信号。测试声音记录在KEMAR人体模型中，两个客观指标，即信噪比（SNRi）和分段SNR（segSNR（i））的提高，用于性能评估。实验结果表明，当输入SNR在-10至+ 5dB范围内时，BSL的精度在90-100％范围内。在餐厅场景中，在交谈中，对角调整算法和固定对角转向算法之间的平均差异（对于-15至+ 5dB输入SNR），SNRi的平均差异为0.203-0.937dB，segSNR（i）的差异为0.052-0.437dB，并且在开车时聆听的情况下，SNRi的差异为0.387-0.835dB，segSNR（i）的差异为0.259-1.175dB。此外，在开车时，双耳波束成形算法的BSL开启和BSL开启情况之间的平均差异在SNRi时为1.631-4.246dB，在segSNR（i）中为0.574-2.784dB。 。在所有测试条件下，经过调整的对角线转向和BSL算法比常规算法更能改善指标值。结合了提出的BSL和对角转向算法的双耳波束成形算法，有望在嘈杂的情况下提高双耳助听器的性能。

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