Sokolova Alice, Sengupta Dhiman, Chen Kuan-Lin, Gupta Rajesh, Aksanli Baris, Harris Fredric, Garudadri Harinath
Department of Electrical and Computer Engineering, UC San Diego, La Jolla, CA, USA.
Department of Electrical and Computer Engineering, San Diego State University, San Diego, CA, USA.
Conf Rec Asilomar Conf Signals Syst Comput. 2021 Oct-Nov;2021:1436-1442. doi: 10.1109/IEEECONF53345.2021.9723257.
The frequency-dependent nature of hearing loss poses many challenges for hearing aid design. In order to compensate for a hearing aid user's unique hearing loss pattern, an input signal often needs to be separated into frequency bands, or channels, through a process called sub-band decomposition. In this paper, we present a real-time filter bank for hearing aids. Our filter bank features 10 channels uniformly distributed on the logarithmic scale, located at the standard audiometric frequencies used for the characterization and fitting of hearing aids. We obtained filters with very narrow passbands in the lower frequencies by employing multi-rate signal processing. Our filter bank offers a 9.1× reduction in complexity as compared to conventional signal processing. We implemented our filter bank on Open Speech Platform, an open-source hearing aid, and confirmed real-time operation.
听力损失的频率依赖性给助听器设计带来了诸多挑战。为了补偿助听器用户独特的听力损失模式，通常需要通过一种称为子带分解的过程将输入信号分离成频带或通道。在本文中，我们提出了一种用于助听器的实时滤波器组。我们的滤波器组具有10个通道，在对数尺度上均匀分布，位于用于助听器特性描述和适配的标准听力测试频率处。通过采用多速率信号处理，我们在较低频率获得了具有非常窄通带的滤波器。与传统信号处理相比，我们的滤波器组在复杂度上降低了9.1倍。我们在开源助听器开放语音平台上实现了我们的滤波器组，并证实了其实时运行。
