Bissmeyer Susan R S, Goldsworthy Raymond L
Caruso Department of Otolaryngology, Caruso Center for Childhood Communication, University of Southern California, 806 West Adams Boulevard, Los Angeles, California 90007, USA.
J Acoust Soc Am. 2017 Sep;142(3):1441. doi: 10.1121/1.5002691.
Hearing loss greatly reduces an individual's ability to comprehend speech in the presence of background noise. Over the past decades, numerous signal-processing algorithms have been developed to improve speech reception in these situations for cochlear implant and hearing aid users. One challenge is to reduce background noise while not introducing interaural distortion that would degrade binaural hearing. The present study evaluates a noise reduction algorithm, referred to as binaural Fennec, that was designed to improve speech reception in background noise while preserving binaural cues. Speech reception thresholds were measured for normal-hearing listeners in a simulated environment with target speech generated in front of the listener and background noise originating 90° to the right of the listener. Lateralization thresholds were also measured in the presence of background noise. These measures were conducted in anechoic and reverberant environments. Results indicate that the algorithm improved speech reception thresholds, even in highly reverberant environments. Results indicate that the algorithm also improved lateralization thresholds for the anechoic environment while not affecting lateralization thresholds for the reverberant environments. These results provide clear evidence that this algorithm can improve speech reception in background noise while preserving binaural cues used to lateralize sound.
听力损失会极大地降低个体在存在背景噪声的情况下理解语音的能力。在过去几十年中，已经开发了许多信号处理算法，以改善人工耳蜗和助听器使用者在这些情况下的语音接收。一个挑战是降低背景噪声，同时不引入会降低双耳听力的双耳失真。本研究评估了一种降噪算法，称为双耳芬尼克算法，其设计目的是在保留双耳线索的同时改善背景噪声中的语音接收。在模拟环境中，对听力正常的听众测量语音接收阈值，目标语音在听众前方生成，背景噪声来自听众右侧90°。还在存在背景噪声的情况下测量了定位阈值。这些测量在消声和混响环境中进行。结果表明，该算法提高了语音接收阈值，即使在高度混响的环境中也是如此。结果表明，该算法还提高了消声环境中的定位阈值，同时不影响混响环境中的定位阈值。这些结果提供了明确的证据，表明该算法可以在保留用于声音定位的双耳线索的同时，改善背景噪声中的语音接收。
