Jong Hee Han

Clinical evaluation of the performance of a blind source separation algorithm combining beamforming and independent component analysis in hearing aid use

There have been several reports on improved blind source separation algorithms that combine beamforming and independent component analysis. However, none of the prior reports verified the clinical efficacy of such combinational algorithms in real hearing aid situations. In the current study, we evaluated the clinical efficacy of such a combinational algorithm using the mean opinion score and speech recognition threshold tests in various types of real-world hearing aid situations involving environmental noise. Parameters of the testing algorithm were adjusted to match the geometric specifications of the real behind-the-ear type hearing aid housing. The study included 15 normal-hearing volunteers and 15 hearing-impaired patients. Experimental results demonstrated that the testing algorithm improved the speech intelligibility of all of the participants in noisy environments, and the clinical efficacy of the combinational algorithm was superior to either the beamforming or independent component analysis algorithms alone. Despite the computational complexity of the testing algorithm, our experimental results and the rapid enhancement of hardware technology indicate that the testing algorithm has the potential to be applied to real hearing aids in the near future, thereby improving the speech intelligibility of hearing-impaired patients in noisy environments.

A high performance hearing aid system with fully programmable ultra low power DSP

This paper presents the design of fully programmable digital signal processor for the hearing aid system and optimized implementation of digital hearing aid algorithms. The average performance of the developed processor is measured by performing Fast Fourier Transform (FFT) algorithm. The proposed applications such as variable multiband loudness compensation algorithm with wide dynamic range compression and sub-band based adaptive feedback cancellation algorithm are optimized for real-time processing by exploiting the data and instruction parallelism of the developed processor. The results show that the computational ability and power consumption of the developed processor are suitable to use for the hearing aid system. The optimization achieves that the computational time to perform the full applications on the processor takes only under 40% of the constraint for real-time processing.

Development of a speech-distortionless beamformer for two-microphone digital hearing aids

To enhance noise reduction performance for digital hearing aids (DHA), this study proposes a speech-distortionless beamformer which is realized by a sequential processing of fractional delay, subtraction and integration (FDSI). A Simulink model of this beamformer was constructed and its performance of speech quality enhancement was evaluated in various noisy circumstances including babble, car and traffic noises. In this simulation, null direction of the beamformer was fixed at 120° azimuth and noise source position was altered from 100 to 140° azimuth. The distance between two microphones also varies from 8 to 20 mm. Compared to conventional beamformers, the FDSI beamformer showed higher frequency-weighted segmental SNR (fwsegSNR) and lower weighted spectral slope (WSS) while perceptual evaluation of speech quality (PESQ) was almost same in every beamformer. These results imply that speech distortion was significantly reduced. Therefore, the FDSI beamformer has great promising for speech quality enhancement in DHA.

A Study on the Performance of Companding Algorithms for Digital Hearing Aid Users

Companding algorithms have been used to enhance speech recognition in noise for cochlea implant users. The efficiency of using companding for digital hearing aid users is not yet validated. The purpose of this study is to evaluate the performance of the companding for digital hearing aid users in the various hearing loss cases. Using HeLPS, a hearing loss simulator, two different sensorinerual hearing loss conditions were simulated; mild gently sloping hearing loss(HL1) and moderate to steeply sloping hearing loss(HL2). In addition, a non-linear compression was simulated to compensate for hearing loss using national acoustic laboratories-non-linear version 1(NAL-NL1) in HeLPS. In companding, the following four different companding strategies were used changing Q values(q1, q2) of pre-filter(F filter) and post filter(G filter). Firstly, five IEEE sentences which were presented with speech-shaped noise at different SNRs(0, 5, 10, 15 dB) were processed by the companding. Secondly, the processed signals were applied to HeLPS. For comparison, signals which were not processed by companding were also applied to HeLPS. For the processed signals, log-likelihood ratio(LLR) and cepstral distance(CEP) were measured for evaluation of speech quality. Also, fourteen normal hearing listeners performed speech reception threshold(SRT) test for evaluation of speech intelligibility. As a result of this study, the processed signals with the companding and NAL-NL1 have performed better than that with only NAL-NL1 in the sensorineural hearing loss conditions. Moreover, the higher ratio of Q values showed better scores in LLR and CEP. In the SRT test, the processed signals with companding(SRT