基于双传感器频域最小方差(FMV)波束形成算法的噪声语音感知

Jeffery B. Larsen, C. Lansing, R. Bilger, B. Wheeler, Sandeep A Phatak, M. Lockwood, W. O’Brien, A. Feng
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引用次数: 1

摘要

对基于双传感器的频域最小方差波束形成算法(FMV)在多重干扰下提取信号的性能进行了评估。语音接收阈值(SRT)和语音清晰度测量来自听力正常或轻度至中度感音神经性听力损失的听者。单词和句子长度刺激通过FMV算法、定向麦克风或简单的延迟和波束形成器进行处理。听者对语音清晰度的评分、正确重复单词的百分比以及在四种竞争信号下单词和句子的阈值表明,FMV在不同的听音环境中提供了显著的性能优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speech perception in noise with a two-sensor frequency-domain minimum-variance (FMV) beamforming algorithm
The performance of a two-sensor based, frequency-domain minimum-variance beamforming algorithm (FMV) to extract a signal in the presence of multiple interferers was evaluated. Speech reception thresholds (SRT) and speech intelligibility measures were obtained from listeners with normal hearing or with mild-to-moderate sensorineural hearing loss. Word and sentence length stimuli were processed through the FMV algorithm, directional microphones alone, or with a simple delay-and-sum beamformer. Listener’s ratings of speech intelligibility, percent of words repeated correctly, and threshold for words and sentences in the presence of four competing signals showed the FMV to provide significant performance benefits across different listening environments.
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