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

Howling and Entrainment in Hearing Aids: A Review

This review focuses on howling and entrainment artifacts in digital hearing aids. The howling may occur (especially at high gains), essentially due to the close proximity of the input microphone and the output loudspeaker. The entrainment, on the other hand, occurs when the input to the hearing aids is periodic, for example, music signals or alarm signals with strong tonal characteristics. We give details on methods for howling avoidance, which are mainly based on adaptive filtering-based acoustic feedback cancellation. We also give an overview of many recent works on entrainment in hearing aids. Finally, we remark that efficient acoustic feedback cancellation scheme which can avoid howling, can also well manage the entrainment artifact

Optimal Step Size Technique for Frequency Domain and Partition Block Adaptive Filters for PEM based Acoustic Feedback Cancellation

The adaptive filtering approach has been commonly used to perform acoustic feedback cancellation (AFC) in digital hearing-aids due to its reliable performance and feasibility. Because the loudspeaker and microphone are close together in hearing aids, the corresponding signals are highly correlated, resulting in biased estimation if adaptive filters are used. This problem can be addressed with the help of the decorrelation prefilter by incorporating the Prediction Error Method (PEM) technique into AFC. Frequency-Domain Adaptive Filters (FDAF) are preferable over the time-domain implementation to achieve better performance in terms of convergence and computational complexity. In addition, Partition-Block Frequency-Domain Adaptive Filters (PBFDAF) offers low processing delay. However, because of their fixed step-size, there is a trade-off between initial convergence and steady-state misalignment in the widely used frequency-domain algorithms. While Variable Step-Size (VSS) algorithms can help with this issue, VSS techniques for frequency-domain algorithms have not been extensively studied in the context of PEM-AFC. Hence, in this paper, we presented an Optimal Step-Size (OSS) technique for both the FDAF-PEM_AFC and PBFDAF-PEM_AFC algorithms to simultaneously accomplish fast convergence and minimal steady-state error. A Feedback Path Change Detector (FPCD) was also incorporated into the proposed algorithms to address the problem of convergence in non-stationary feedback paths. The results of simulations show that the proposed algorithms are clearly superior, and they are encouraging

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

Adaptive Feedback Cancellation in Hearing Aids

Acoustic feedback is a well-known phenomenon in hearing aids and public address systems. Under certain conditions it causes the so-called howling effect, which is highly annoying for the hearing aid user and limits the maximum amplification of the hearing aid. The most common choice to prevent howling is the adaptive feedback cancellation algorithm, which is able to completely eliminate the feedback signal. However, standard adaptive feedback cancellation algorithms suffer from a biased adaptation if the input signal is spectrally colored, as it is for speech and music signals. Due to this bias distortion artifacts (entrainment) are generated and consequently, the sound quality is significantly reduced. Most of the known methods to reduce the bias have focused on speech signals. However, those methods do not cope with music, since the tonality and correlation are much stronger for such signals. This leads to a higher bias and consequently, to stronger entrainment for music than for speech. Other methods, which deal with music signals, work only satisfactorily when using a very slow adaptation speed. This reduces the ability to react fast to feedback path changes. Hence, howling occurs for a longer time when the feedback path is changing. In this thesis, a new sub-band adaptive feedback cancellation system for hearing aid applications is proposed. It combines decorrelation methods with a new realization of a non-parametric variable step size. The adaptation is realized in sub-bands which decreases the computational complexity and increases the adaptation performance of the system simultaneously. The applied decorrelation methods, prediction error filter and frequency shift, are well known approaches to reduce the bias. However, the combination of both is first proposed in this thesis. To apply the proposed step size in the context of adaptive feedback cancellation, a method to estimate the signal power of the desired input signal, i.e., without feedback, also referred to as source signal power is necessary. This estimate is theoretically derived and it is demonstrated that it is a reliabe estimate if the decorrelation methods are additionally applied. In order to further improve the performance of the system three additional control methods are derived: The first one is an impulse detection to detect wideband impulses, which could lead to misadaptation. Secondly, a modified estimate of the source signal power to stabilize the system in case of jarring voices is proposed. Lastly, a correlation detection, which is applied to improve the trade-off between adaptation stability and tracking behavior, is developed. The complete system is optimized and evaluated for several speech and music signals as well as for different feedback scenarios in simulations with feedback paths measured under realistic situations. Additionally, the system is tested by real-time simulations with hearing aid dummies and a torso and head simulator. For both simulation setups hearing loss compensation methods as applied in realistic hearing aids are used. The performance is measured in terms of being able to prevent entrainment (adaptation stability) and reacting to feedback path changes (tracking behavior). The complete adaptive feedback cancellation system shows an excellent performance. Furthermore, the system relies only on few parameters, shows a low computational complexity, and therefore has a strong practical relevance