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“-of-”音处理策略用于人工耳蜗的共振峰优先通道选择。

Formant priority channel selection for an "-of-" sound processing strategy for cochlear implants.

机构信息

Cochlear Implant Processing Laboratory-Center for Robust Speech Systems, University of Texas at Dallas, Richardson, 800 West Campbell Road, Richardson, Texas 75080, USA.

出版信息

J Acoust Soc Am. 2018 Dec;144(6):3371. doi: 10.1121/1.5080257.

Abstract

The Advanced Combination Encoder (ACE) signal processing strategy is used in the majority of cochlear implant (CI) sound processors manufactured by Cochlear Corporation. This "-of-" strategy selects "" out of "" available frequency channels with the highest spectral energy in each stimulation cycle. It is hypothesized that at low signal-to-noise ratio (SNR) conditions, noise-dominant frequency channels are susceptible for selection, neglecting channels containing target speech cues. In order to improve speech segregation in noise, explicit encoding of formant frequency locations within the standard channel selection framework of ACE is suggested. Two strategies using the direct formant estimation algorithms are developed within this study, FACE (formant-ACE) and VFACE (voiced-activated-formant-ACE). Speech intelligibility from eight CI users is compared across 11 acoustic conditions, including mixtures of noise and reverberation at multiple SNRs. Significant intelligibility gains were observed with VFACE over ACE in 5 dB babble noise; however, results with FACE/VFACE in all other conditions were comparable to standard ACE. An increased selection of channels associated with the second formant frequency is observed for FACE and VFACE. Both proposed methods may serve as potential supplementary channel selection techniques for the ACE sound processing strategy for cochlear implants.

摘要

高级组合编码器(ACE)信号处理策略被应用于 Cochlear 公司生产的大多数人工耳蜗(CI)声音处理器中。这种“-of-”策略在每个刺激周期中从“可用”的频率通道中选择具有最高光谱能量的“”。假设在低信噪比(SNR)条件下,噪声主导的频率通道容易被选中,而忽略包含目标语音线索的通道。为了提高噪声中的语音分离度,建议在 ACE 的标准通道选择框架内明确编码共振峰频率位置。本研究中开发了两种使用直接共振峰估计算法的策略,即 FACE(共振峰-ACE)和 VFACE(有声激活共振峰-ACE)。在包括多个 SNR 的噪声和混响混合物的 11 种声学条件下,比较了 8 名 CI 用户的语音可懂度。在 5dB 背景噪声下,与 ACE 相比,VFACE 观察到语音可懂度显著提高;然而,在所有其他条件下,FACE/VFACE 的结果与标准 ACE 相当。FACE 和 VFACE 观察到与第二共振峰相关的通道选择增加。这两种方法都可以作为 ACE 声音处理策略的潜在补充通道选择技术,用于人工耳蜗。

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