Department of Bio-Medical Engineering, Faculty of Engineering, Tel-Aviv University, Israel.
J Acoust Soc Am. 2012 Sep;132(3):1718-31. doi: 10.1121/1.4739441.
A common complaint of the hearing impaired is the inability to understand speech in noisy environments even with their hearing assistive devices. Only a few single-channel algorithms have significantly improved speech intelligibility in noise for hearing-impaired listeners. The current study introduces a cochlear noise reduction algorithm. It is based on a cochlear representation of acoustic signals and real-time derivation of a binary speech mask. The contribution of the algorithm for enhancing word recognition in noise was evaluated on a group of 42 normal-hearing subjects, 35 hearing-aid users, 8 cochlear implant recipients, and 14 participants with bimodal devices. Recognition scores of Hebrew monosyllabic words embedded in Gaussian noise at several signal-to-noise ratios (SNRs) were obtained with processed and unprocessed signals. The algorithm was not effective among the normal-hearing participants. However, it yielded a significant improvement in some of the hearing-impaired subjects under different listening conditions. Its most impressive benefit appeared among cochlear implant recipients. More than 20% improvement in recognition score of noisy words was obtained by 12, 16, and 26 hearing-impaired at SNR of 30, 24, and 18 dB, respectively. The algorithm has a potential to improve speech intelligibility in background noise, yet further research is required to improve its performances.
听力障碍者的常见抱怨之一是，即使使用助听设备，他们也无法在嘈杂环境中理解言语。只有少数单通道算法能显著提高听力障碍者在噪声环境中的言语可懂度。本研究介绍了一种耳蜗降噪算法。它基于声学信号的耳蜗表示和实时推导二进制语音掩蔽。该算法对一组 42 名正常听力受试者、35 名助听器使用者、8 名耳蜗植入者和 14 名双模使用者的增强噪声中单词识别能力进行了评估。通过处理和未处理的信号，在几个信噪比 (SNR) 下获得了希伯来语单音节词在高斯噪声中的识别分数。该算法在正常听力参与者中无效。然而，它在不同的听力障碍者在不同的听力条件下产生了显著的改善。其最令人印象深刻的好处出现在耳蜗植入者中。12、16 和 26 名听力障碍者在 SNR 为 30、24 和 18dB 的情况下，噪声词的识别得分分别提高了 20%以上。该算法有可能提高背景噪声中的言语可懂度，但需要进一步研究以提高其性能。
