Improvement of Speech Perception for Hearing-Impaired Listeners

Hearing impairment is becoming a prevalent health problem affecting 5% of world adult populations. Hearing aids and cochlear implant already play an essential role in helping patients over decades, but there are still several open problems that prevent them from providing the maximum benefits. Financial and discomfort reasons lead to only one of four patients choose to use hearing aids; Cochlear implant users always have trouble in understanding speech in a noisy environment. In this dissertation, we addressed the hearing aids limitations by proposing a new hearing aid signal processing system named Open-source Self-fitting Hearing Aids System (OS SF hearing aids). The proposed hearing aids system adopted the state-of-art digital signal processing technologies, combined with accurate hearing assessment and machine learning based self-fitting algorithm to further improve the speech perception and comfort for hearing aids users. Informal testing with hearing-impaired listeners showed that the testing results from the proposed system had less than 10 dB (by average) difference when compared with those results obtained from clinical audiometer. In addition, Sixteen-channel filter banks with adaptive differential microphone array provides up to six-dB SNR improvement in the noisy environment. Machine-learning based self-fitting algorithm provides more suitable hearing aids settings. To maximize cochlear implant users’ speech understanding in noise, the sequential (S) and parallel (P) coding strategies were proposed by integrating high-rate desynchronized pulse trains (DPT) in the continuous interleaved sampling (CIS) strategy. Ten participants with severe hearing loss participated in the two rounds cochlear implants testing. The testing results showed CIS-DPT-S strategy significantly improved (11%) the speech perception in background noise, while the CIS-DPT-P strategy had a significant improvement in both quiet (7%) and noisy (9%) environment

Power Consumption of Digital Hearing Aid Computations Using Customized Numerical Representations

We investigate the impact of numerical representation on the power consumption of digital hearing aids. A fundamental building block, a non-linear amplifier, is implemented using traditional 16-bit linear or customized 9-bit logarithmic and 10-bit floating point numerical representations. An individual channel of a multi-channel hearing aid is constructed, targeting both FPGA and ASIC deployment options. Using signal transition counts in the post-synthesis simulation to model power consumption, we compare the relative power consumption of the non-linear amplifiers, a full hearing aid channel, and the complete hearing aid signal processing for these three numerical representations. Our results show that for the non-linear amplifier, the logarithmic and floating-point representations provide significant savings over a traditional linear representation. However, since the total power consumption is dominated by the FIR filters, the total power saving is on the order of the filters

Electroacoustic and Behavioural Evaluation of Hearing Aid Digital Signal Processing Features

Modern digital hearing aids provide an array of features to improve the user listening experience. As the features become more advanced and interdependent, it becomes increasingly necessary to develop accurate and cost-effective methods to evaluate their performance. Subjective experiments are an accurate method to determine hearing aid performance but they come with a high monetary and time cost. Four studies that develop and evaluate electroacoustic hearing aid feature evaluation techniques are presented. The first study applies a recent speech quality metric to two bilateral wireless hearing aids with various features enabled in a variety of environmental conditions. The study shows that accurate speech quality predictions are made with a reduced version of the original metric, and that a portion of the original metric does not perform well when applied to a novel subjective speech quality rating database. The second study presents a reference free (non-intrusive) electroacoustic speech quality metric developed specifically for hearing aid applications and compares its performance to a recent intrusive metric. The non-intrusive metric offers the advantage of eliminating the need for a shaped reference signal and can be used in real time applications but requires a sacrifice in prediction accuracy. The third study investigates the digital noise reduction performance of seven recent hearing aid models. An electroacoustic measurement system is presented that allows the noise and speech signals to be separated from hearing aid recordings. It is shown how this can be used to investigate digital noise reduction performance through the application of speech quality and speech intelligibility measures. It is also shown how the system can be used to quantify digital noise reduction attack times. The fourth study presents a turntable-based system to investigate hearing aid directionality performance. Two methods to extract the signal of interest are described. Polar plots are presented for a number of hearing aid models from recordings generated in both the free-field and from a head-and-torso simulator. It is expected that the proposed electroacoustic techniques will assist Audiologists and hearing researchers in choosing, benchmarking, and fine-tuning hearing aid features

Comparative study of analog and digital hearing aids

The purpose of the present study was to determine if objective and/or subjective differences between analog and digital hearing aids exist when blinding is utilized in the protocol and circuitry is controlled. Ten normal hearing and seven hearing impaired subjects were monaurally fitted with analog and digital hearing aids. Probe microphone measures were obtained at the plane of the tympanic membrane at two output levels (40 dB SPL and 70 dB SPL). Listener performance in quiet was evaluated via word recognition testing, listener performance in noise was evaluated via the Hearing in Noise Test, and listener preference was evaluated via a questionnaire. Results indicated similar performance for all objective and subjective tasks for both hearing aids with the exception of better performance in quiet at the 40 dB SPL presentation level with the analog hearing aid for the hearing impaired group. These results indicate that listeners performed as well or significantly better with the analog hearing aid than with the digital hearing aid. Furthermore, future investigation is recommended to evaluate the effectiveness of some features available on digital hearing aids that are not available on analog hearing aids, such as expansion and noise reduction

Further simulations of the effect of cochlear-implant pre-processing and head movement on interaural level differences

We simulated the effect of several automatic gain control (AGC) and AGC-like systems and head movement on the output levels, and resulting interaural level differences (ILDs) produced by bilateral cochlear-implant (CI) processors. The simulated AGC systems included unlinked AGCs with a range of parameter settings, linked AGCs, and two proprietary multi-channel systems used in contemporary CIs. The results show that over the range of values used clinically, the parameters that most strongly affect dynamic ILDs are the release time and compression ratio. Linking AGCs preserves ILDs at the expense of monaural level changes and, possibly, comfortable listening level. Multichannel AGCs can whiten output spectra, and/or distort the dynamic changes in ILD that occur during and after head movement. We propose that an unlinked compressor with a ratio of approximately 3:1 and a release time of 300-500 ms can preserve the shape of dynamic ILDs, without causing large spectral distortions or sacrificing listening comfort

Adaptive gain and filtering circuit for a sound reproduction system

Adaptive compressive gain and level dependent spectral shaping circuitry for a hearing aid include a microphone to produce an input signal and a plurality of channels connected to a common circuit output. Each channel has a preset frequency response. Each channel includes a filter with a preset frequency response to receive the input signal and to produce a filtered signal, a channel amplifier to amplify the filtered signal to produce a channel output signal, a threshold register to establish a channel threshold level, and a gain circuit. The gain circuit increases the gain of the channel amplifier when the channel output signal falls below the channel threshold level and decreases the gain of the channel amplifier when the channel output signal rises above the channel threshold level. A transducer produces sound in response to the signal passed by the common circuit output