Department of Biomedical Engineering, College of Health Science, Yonsei University, 234 Maeji-ri, Heungup-myun, Wonju, Kangwon-do 220-710, Republic of Korea.
Comput Math Methods Med. 2013;2013:153039. doi: 10.1155/2013/153039. Epub 2013 Apr 17.
We propose a new active nonlinear model of the frequency response of the basilar membrane in biological cochlea called the simple dual path nonlinear (SDPN) model and a novel sound processing strategy for cochlear implants (CIs) based upon this model. The SDPN model was developed to utilize the advantages of the level-dependent frequency response characteristics of the basilar membrane for robust formant representation under noisy conditions. In comparison to the dual resonance nonlinear model (DRNL) which was previously proposed as an active nonlinear model of the basilar membrane, the SDPN model can reproduce similar level-dependent frequency responses with a much simpler structure and is thus better suited for incorporation into CI sound processors. By the analysis of dominant frequency component, it was confirmed that the formants of speech are more robustly represented after frequency decomposition by the nonlinear filterbank using SDPN, compared to a linear bandpass filter array which is used in conventional strategies. Acoustic simulation and hearing experiments in subjects with normal hearing showed that the proposed strategy results in better syllable recognition under speech-shaped noise compared to the conventional strategy based on fixed linear bandpass filters.
我们提出了一种新的生物耳蜗基底膜频率响应的主动非线性模型,称为简单双路径非线性(SDPN)模型,并基于该模型提出了一种新的耳蜗植入(CI)声音处理策略。SDPN 模型的开发是为了利用基底膜频率响应特性的水平依赖性,在噪声环境下实现稳健的共振峰表示。与之前作为基底膜主动非线性模型提出的双共振非线性模型(DRNL)相比,SDPN 模型具有更简单的结构,可以复制相似的水平依赖性频率响应,因此更适合纳入 CI 声音处理器。通过对主导频率分量的分析,确认在使用 SDPN 的非线性滤波器组进行频率分解后,语音的共振峰比传统策略中使用的线性带通滤波器阵列更稳健地表示。在正常听力受试者的声学模拟和听力实验中,与基于固定线性带通滤波器的传统策略相比,所提出的策略在语音噪声下的音节识别性能更好。