Control of feedback for assistive listening devices

Acoustic feedback refers to the undesired acoustic coupling between the loudspeaker and microphone in hearing aids. This feedback channel poses limitations to the normal operation of hearing aids under varying acoustic scenarios. This work makes contributions to improve the performance of adaptive feedback cancellation techniques and speech quality in hearing aids. For this purpose a two microphone approach is proposed and analysed; and probe signal injection methods are also investigated and improved upon

Doctor of Philosophy

dissertationHearing aids suffer from the problem of acoustic feedback that limits the gain provided by hearing aids. Moreover, the output sound quality of hearing aids may be compromised in the presence of background acoustic noise. Digital hearing aids use advanced signal processing to reduce acoustic feedback and background noise to improve the output sound quality. However, it is known that the output sound quality of digital hearing aids deteriorates as the hearing aid gain is increased. Furthermore, popular subband or transform domain digital signal processing in modern hearing aids introduces analysis-synthesis delays in the forward path. Long forward-path delays are not desirable because the processed sound combines with the unprocessed sound that arrives at the cochlea through the vent and changes the sound quality. In this dissertation, we employ a variable, frequency-dependent gain function that is lower at frequencies of the incoming signal where the information is perceptually insignificant. In addition, the method of this dissertation automatically identifies and suppresses residual acoustical feedback components at frequencies that have the potential to drive the system to instability. The suppressed frequency components are monitored and the suppression is removed when such frequencies no longer pose a threat to drive the hearing aid system into instability. Together, the method of this dissertation provides more stable gain over traditional methods by reducing acoustical coupling between the microphone and the loudspeaker of a hearing aid. In addition, the method of this dissertation performs necessary hearing aid signal processing with low-delay characteristics. The central idea for the low-delay hearing aid signal processing is a spectral gain shaping method (SGSM) that employs parallel parametric equalization (EQ) filters. Parameters of the parametric EQ filters and associated gain values are selected using a least-squares approach to obtain the desired spectral response. Finally, the method of this dissertation switches to a least-squares adaptation scheme with linear complexity at the onset of howling. The method adapts to the altered feedback path quickly and allows the patient to not lose perceivable information. The complexity of the least-squares estimate is reduced by reformulating the least-squares estimate into a Toeplitz system and solving it with a direct Toeplitz solver. The increase in stable gain over traditional methods and the output sound quality were evaluated with psychoacoustic experiments on normal-hearing listeners with speech and music signals. The results indicate that the method of this dissertation provides 8 to 12 dB more hearing aid gain than feedback cancelers with traditional fixed gain functions. Furthermore, experimental results obtained with real world hearing aid gain profiles indicate that the method of this dissertation provides less distortion in the output sound quality than classical feedback cancelers, enabling the use of more comfortable style hearing aids for patients with moderate to profound hearing loss. Extensive MATLAB simulations and subjective evaluations of the results indicate that the method of this dissertation exhibits much smaller forward-path delays with superior howling suppression capability

An Explicit Criterion for Adaptive Periodic Noise Canceller Robustness Applied to Feedback Cancellation

This paper addresses the issue of robustness of an LMS-driven Adaptive Periodic Noise Canceller (APNC) in a closed-loop system. By adopting an analysis based on H-infinity theory, expressions are given under which the APNC, driven by the LMS algorithm, will exhibit robust performance properties. Simulation results are used to verify the analysis. Comparison is also made with an expression for stepsize derived for the less stringent bound of algorithm stability to demonstrate the strictness of the robustness criterion

Residual feedback suppression with extended model-based postfilters

When designing closed-loop electro-acoustic systems, which can commonly be found in hearing aids or public address systems, the most challenging task is canceling and/or suppressing the feedback caused by the acoustic coupling of the transducers of such systems. In many applications, feedback cancelation based on adaptive filters is used for this purpose. However, due to computational complexity such a feedback canceler is often limited in the length of the filter’s impulse response. Consequently, a residual feedback, which is still audible and may lead to system instability, remains in most cases. In this work, we present enhancements for model-based postfilters based on a priori knowledge of the feedback path which can be used cooperatively with the adaptive filter-based feedback cancelation system to suppress residual feedback and improve the overall feedback reduction capability. For this, we adapted an existing reverberation model such that our model additionally considers the presence and the performance of the adaptive filter. We tested the effectiveness of our approach by means of both objective and subjective evaluations

A Survey on Application Specific Processor Architectures for Digital Hearing Aids

On the one hand, processors for hearing aids are highly specialized for audio processing, on the other hand they have to meet challenging hardware restrictions. This paper aims to provide an overview of the requirements, architectures, and implementations of these processors. Special attention is given to the increasingly common application-specific instruction-set processors (ASIPs). The main focus of this paper lies on hardware-related aspects such as the processor architecture, the interfaces, the application specific integrated circuit (ASIC) technology, and the operating conditions. The different hearing aid implementations are compared in terms of power consumption, silicon area, and computing performance for the algorithms used. Challenges for the design of future hearing aid processors are discussed based on current trends and developments

DIGITAL HEARING AID SIGNAL PROCESSING SYSTEM USING ANDROID PHONE

Objective: The objective of this research is to propose an Android-based digital hearing aid signal processing algorithm with following key features:(1) Regenerated audio match the patient-specific pattern of hearing loss, (2) noise reduction, and (3) provide flexibility to the users.Methods: The proposed signal processing algorithm is designed based on the specific hearing loss of the hearing disorder patient using inverse Fouriertransform; besides, noise reduction feature is included in the digital algorithm design as well. Proposed digital algorithm has been implemented intoan Android-based smartphone and its performance has been tested under real-time condition.Results: Simulation results show that the frequency response of the proposed digital hearing aid signal processing algorithm is in agreement withthe initial theoretical design that was carried out based on the hearing impaired patient’s audiogram. The proposed algorithm has been implementedin the Android-based smartphone and tested in real time. Results show that most of the patients are satisfied with the regenerated audio quality.According to patient’s comments, the regenerated audio is clear and the users are allowed to control the volume level. Besides, no obvious hearinglatency can be detected.Conclusion: Audio signals generated by the proposed digital signal processing algorithm show similar audio signal frequency response in boththeoretical design and MATLAB simulation results. The only difference between the design and simulation results is the amplification levels. Theproposed algorithm provides flexibility to the users by allowing them to choose the desired amplification level. In real-time testing, the proposedAndroid-based digital hearing aid is able to reduce noise level from the surrounding and the output processed speech match the patient-specifichearing loss

Manipulation of Auditory Feedback in Individuals with Normal Hearing and Hearing Loss

Auditory feedback, the hearing of one’s own voice, plays an important role in the detection of speech errors and the regulation of speech production. The limited auditory cues available with a hearing loss can reduce the ability of individuals with hearing loss to use their auditory feedback. Hearing aids are a common assistive device that amplifies inaudible sounds. Hearing aids can also change auditory feedback through digital signal processing, such as frequency lowering. Frequency lowering moves high frequency information of an incoming auditory stimulus into a lower frequency region where audibility may be better. This can change how speech sounds are perceived. For example, the high frequency information of /s/ is moved closer to the lower frequency area of /ʃ/. As well, real-time signal processing in a laboratory setting can also manipulate various aspects of speech cues, such as intensity and vowel formants. These changes in auditory feedback may result in changes in speech production as the speech motor control system may perceive these perturbations as speech errors. A series of experiments were carried out to examine changes in speech production as a result of perturbations in the auditory feedback in individuals with normal hearing and hearing loss. Intensity and vowel formant perturbations were conducted using real-time signal processing in the laboratory. As well, changes in speech production were measured using auditory feedback that was processed with frequency lowering technology in hearing aids. Acoustic characteristics of intensity of vowels, sibilant fricatives, and first and second formants were analyzed. The results showed that the speech motor control system is sensitive to changes in auditory feedback because perturbations in auditory feedback can result in changes in speech production. However, speech production is not completely controlled by auditory feedback and other feedback systems, such as the somatosensory system, are also involved. An impairment of the auditory system can reduce the ability of the speech motor control system to use auditory feedback in the detection of speech errors, even when aided with hearing aids. Effects of frequency lowering in hearing aids on speech production depend on the parameters used and acclimatization time