Complexity-effective dynamic range compression for digital hearing aids

Chang, Kuang-Yi; Kuo, Yu‐Ting; Lin, Tay-Jyi; Li, Youfu

doi:10.1109/iscas.2010.5537181

Cited by 11 publications

(5 citation statements)

References 7 publications

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“…Note that the result of SFB is not included in Table VII because the filter banks in the literature [7]- [14] have all considered AFB only. Moreover, SFB in a hearing aid SoC will likely be merged with dynamic range compressors for further optimization [6], [26]. The comparison results in Table VII validate the effectiveness of the proposed quasi-ANSI AFB.…”

Section: The Optimized Low-power Architecturementioning

confidence: 74%

10-ms 18-Band Quasi-ANSI S1.11 1/3-Octave Filter Bank for Digital Hearing Aids

Chang

Chuang

et al. 2013

IEEE Trans. Circuits Syst. I

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The ANSI S1.11 1/3-octave filter bank is suitable for digital hearing aids, but its large group delay and high computational complexity complicate matters considerably. This study presents a 10-ms 18-band quasi-ANSI S1.11 1/3-octave filter bank for processing 24 kHz audio signals. We first discuss a filter order optimization algorithm to define the quasi-ANSI filters. The group delay constraint of filters is limited to 10 ms. The proposed design adopts an efficient prescription-fitting algorithm to reduce inter-band interference, enabling the proposed quasi-ANSI filter bank to compensate any type of hearing loss (HL) using the NAL-NL1 or HSE prescription formulas. Simulation results reveal that the maximum matching error in the prescriptions of the mild HL, moderate HL, and severe-to-profound HL is less than 1.5 dB. This study also investigates the complexity-effective multirate IFIR quasi-ANSI filter bank. For an 18-band digital hearing aid with a 24 kHz sampling rate, the proposed architecture eliminates approximately 93% of the multiplications and up to 74% of the storage elements, compared with a parallel FIR filters architecture. The proposed analysis filter bank (AFB) was designed in UMC 90 nm CMOS high-VT technology, and on the basis of post-layout simulations, it consumes 73 W V). By voltage scaling (to 0.6 V), the simulation results show that the power consumption decreases to 27 W, which is approximately 30% of that consumed by the most energy-efficient AFB available in the literature for use in hearing aids.Index Terms-Filter bank, hearing aid, low group delay.

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Section: The Optimized Low-power Architecturementioning

confidence: 74%

10-ms 18-Band Quasi-ANSI S1.11 1/3-Octave Filter Bank for Digital Hearing Aids

Chang

Chuang

et al. 2013

IEEE Trans. Circuits Syst. I

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“…The general requirement of less than 12 ms [2] prevents the loss of visual cues (un-synchronized) with respect to hearing. Stone and Moore [16], [17] indicated that a delay of 20-30 ms can be judged as objectionable for mild-to-moderate hearing loss. The popularity of open-canal (OC) fitting hearing aids, which leave the ear canal much more open than traditional close-fitting ear-molds, makes hearing aid delays even more concerning.…”

Section: Fig 3 Matching Capability Comparisons For Different Types mentioning

confidence: 99%

Low-Power High-Speed Amplification Using FilterBank for Digital Hearing AIDS

Rajalakshmi¹,

Gunasekaran²

2016

IJMSR

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-The ANSI S1.11 1/3-octave filter bank is suitable for digital hearing aids, but its large group delay and high compu-tational complexity complicate matters considerably. This study presents a 10-ms 18-band quasi-ANSI S1.11 1/3-octave filter bank for processing 24 kHz audio signals. We first discuss a filter order optimization algorithm to define the quasi-ANSI filters. The group delay constraint of filters is limited to 10 ms. The proposed design adopts an efficient prescription-fitting algorithm to reduce inter-band interference, enabling the proposed quasi-ANSI filter bank to compensate any type of hearing loss (HL) using the NAL-NL1 or HSE prescription formulas. Simulation results re-veal that the maximum matching error in the prescriptions of the mild HL, moderate HL, and severe-to-profound HL is less than 1.5 dB. This study also investigates the complexity-effective multirate IFIR quasi-ANSI filter bank. For an 18-band digital hearing aid with a 24 kHz sampling rate, the proposed architecture eliminates approximately 93% of the multiplications and up to 74% of the storage elements, compared with a parallel FIR filters architec-ture. The proposed analysis filter bank (AFB) was designed in UMC 90 nm CMOS high-VT technology, and on the basis of postlayout simulations, it consumes 73 W. By voltage scaling (to 0.6 V), the simulation results show that the power consumption decreases to 27 W, which is approximately 30% of that consumed by the most energy-efficient AFB available in the literature for use in hearing aids.Index Terms-Filter bank, hearing aid, low group delay.

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“…Different echo cancellation techniques could be implemented to cancel the echo or feedback [10], [11]. Hearing aids also use compression [4], [5], [6] which basically amplify the low level sounds more than the high level sounds. If the compression is not used the hearing aid will also amplify louder sound which will be painful.…”

Section: Types Of Hearing Aidsmentioning

confidence: 99%

FPGA Prototype Implementation of Digital Hearing Aid from Software to Complete Hardware Design

Buzdar¹,

Latif²,

Sun³

et al. 2016

ijacsa

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Abstract-The design and implementation of digital hearing aids requires a detailed knowledge of various digital signal processing techniques used in hearing aids like Wavelet Transforms, uniform and non-uniform Filter Banks and Fast Fourier Transform (FFT). In this paper the design and development of digital part of hearing aid is divided into three different phases. In the first phase review and Matlab simulation of various signal processing techniques used in the digital hearing aids is presented. In the second phase a software implementation was carried out and the firmware was designed for the Xilinx Microblaze softcore processor system. In the third phase everything was moved into hardware using VHDL hardware description language. The implementation was done on Xilinx Field Programmable Gate Array (FPGA) Development Board.

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Complexity-effective dynamic range compression for digital hearing aids

Cited by 11 publications

References 7 publications

10-ms 18-Band Quasi-ANSI S1.11 1/3-Octave Filter Bank for Digital Hearing Aids

10-ms 18-Band Quasi-ANSI S1.11 1/3-Octave Filter Bank for Digital Hearing Aids

Low-Power High-Speed Amplification Using FilterBank for Digital Hearing AIDS

FPGA Prototype Implementation of Digital Hearing Aid from Software to Complete Hardware Design

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