A PEM-AFROW based algorithm for acoustic feedback control in automotive speech reinforcement systems

In this paper we propose a new variable step-size of the Least-Mean-Square (LMS) algorithm for reducing acoustic feedback in hearing aids. The new variable step-size is designed to approximate the optimum variable step-size that allows the LMS algorithm to decrease its mean-squared error with the fastest rate. The performance of the proposed variable step-size on the acoustic feedback cancellation is compared via computer simulation with those of three other step-size adjustment methods. The comparisons indicate that the new step-size adjustment method has better dynamic and steady state performances than the other methods. In addition, the computation complexity of the new method is relatively low compared with those of the other methods, rendering it more suitable for solving acoustic feedback in hearing aids.

Publication in the conference proceedings of EUSIPCO, Antalya, Turkey, 2005

While several proactive acoustic feedback (Larsen-effect) cancellation schemes have been presented for speech applications with short acoustic feedback paths as encountered in hearing aids, these schemes fail with the long impulse responses inherent to, for instance, public address systems. We derive a new prediction error method (PEM)-based scheme (referred to as PEM-AFROW) which identifies both the acoustic feedback path and the nonstationary speech source model. A cascade of a short- and a long-term predictor removes the coloring and periodicity in voiced speech segments, which account for the unwanted correlation between the loudspeaker signal and the speech source signal. The predictors calculate row operations which are applied to prewhiten the speech source signal, resulting in a least squares system that is solved recursively by means of normalized least mean square or recursive least squares algorithms. Simulations show that this approach is indeed superior to earlier approaches whenever long acoustic channels are dealt with

Publication in the conference proceedings of EUSIPCO, Poznan, Poland, 2007

A probe noise signal can be used in an acoustic feedback cancellation system to prevent biased adaptive estimation of acoustic feedback paths. However, practical experiences and simulation results indicate that whenever a low-level and inaudible probe noise signal is used, the convergence rate of the adaptive estimation is significantly decreased when keeping the steady-state error unchanged. The goal of this work is to derive analytic expressions for the system behavior such as convergence rate and steady-state error for a multiple-microphone and single-loudspeaker audio system, where the acoustic feedback cancellation is carried out using a probe noise signal. The derived results show how different system parameters and signal properties affect the cancellation performance, and the results explain theoretically the decreased convergence rate. Understanding this is important for making further improvements in the existing probe noise approach.

This study introduces a novel online censoring-least mean square (OC-LMS) based acoustic feedback cancellation (AFC) system to eliminate undesired acoustic feedback that causes instability in hearing aids. The performance of the proposed OC-LMS based AFC system is tested on a sample feedback path measured from a behind-the-ear hearing aid and compared with its conventional LMS based version in terms of mean square deviation, misalignment, and added stable gain metrics. Simulation results shows that the proposed AFC system works at higher performance than its LMS based version with fewer data by censoring noninformative data thanks to its censoring mechanism. The proposed novel system will pave the way for the design of wearable hearing aids that work with both high performance and long battery life.

When fitting hearing aids, there are three guidelines that should always be followed by the dispenser: restore audibility; so that the amplified sound is above the user's threshold, limit the output; so that the amplified signal does not exceed the user's discomfort level, and do no harm; so that the amplified signal is not unintentionally or undesirably altered by the hearing aid. The first two of these three guidelines are obvious. The first is to present sounds above the user's threshold of hearing in order to create an acoustic environment with the maximum amount of audible speech cues. The second ensures that discomfort level is not exceeded, so that the user does not wince or remove the hearing aids when loud sounds are present. The third guideline—do no harm—is less obvious. This indicates that it is important that the hearing aids produce no alteration of the signal other than that which the fitter intends. This is a subtle way of saying that, among other things, well-fitted hearing aids should not distort the desired sound. The topic of distortion is the subject of this issue of Trends in Amplification. The intention of this issue is to explain why distortion occurs in some hearing aids; to explain how distortion is measured; to summarize what can be done to prevent distortion; and to summarize the perception of distortion by the hearing aid wearer. Distortion in hearing aids can be broadly defined as the generation of undesired audible components that are present in the output, but which are not present in the input. When distortion occurs, hearing aids produce undesired elements at the output through the interaction of the processed signal with some internal non-linear mechanism. These undesired components may interfere to some degree or other with the reception of sound by the listener. If these added elements are small compared to the overall signal level, they may effectively cause no interference at all. If they are large, they can be so disruptive to the listener that the desired sound becomes irritating or even incomprehensible. All audio systems inevitably contain some amount of distortion. The practical problem for the listener is the type of distortion that is present and the level that is acceptable or tolerable in hearing aids before the distortion becomes disruptive to speech intelligibility and sound quality. It is known that highly distorted speech in quiet can remain intelligible (Licklider, 1946); however, as dispensers often experience, intelligibility is not the only measure of whether or not a user will accept and wear hearing aids. Gabrielsson and Sjogren (1979b) have shown that overall perceived sound quality is important to users when selecting a hearing aid. Punch (1978) has shown that listeners with mild to moderate sensorineural hearing losses retain the same ability to make distinctions in sound quality judgments as listeners with normal hearing. This implies that good sound quality is as equally important and desired by listeners with a hearing impairment as it is for listeners with normal hearing. Three characteristics of distortion in hearing aids modify the sound delivered to the user: the type of distortion, the relative amount of distortion at different frequencies, and the variation of distortion with different input levels. Since the most important goal for fitting hearing aids is to restore or facilitate communication ability, undistorted sound is important for optimum speech intelligibility and sound quality. However, it is important to also recognize that there are other reasons to provide undistorted amplification of sound. For example, undistorted and pleasant reproduction of music may be an important sensory experience for some listeners. This issue concentrates on different types of undesired modification to the waveshape of the sound, primarily by total harmonic distortion (THD) and intermodulation distortion (IMD). However, in a more general sense, any undesired component added to the sound by hearing aids is a form of distortion. Thus, this issue also discusses sound generated by hearing aids with no signal present at the microphone. This artifact is more commonly called internal noise. Internal noise fits within the definition of distortion given earlier, since internal noise is an undesired product generated in the output of hearing aids that is not present at the input. In some cases, distortion and internal noise are so closely linked that they cannot always be separated into discrete entities. For example, instability in the frequency and shape of the clock pulses in a Class D output stage (often loosely called clock jitter) results in distortion of the signal. However, this artifact may be audibly revealed in the output sound primarily as noise, rather than as distortion of the waveform. According to this broad definition of distortion, undesired noises such as “motorboating” and other acoustic feedback oscillations can also be considered to be forms of distortion. However, acoustic feedback and other similar audible artifacts occurring within hearing aids will not be discussed here. These types of distortion have been discussed in detail by Agnew (1996b) in a previous issue of Trends in Amplification. In this issue distortion is discussed in two general categories: Undesired modification of the waveform of the incoming sound by some mechanism occurring within the hearing aids. The severity of this effect may or may not vary with the acoustic level of the incoming sound. This type of audible artifact is generally what most dispensers refer to as “distortion”. This will be the subject of Part I of this issue, and will follow the definition used for distortion in this text. The production of undesired audible components in the output sound, regardless of whether or not there is any acoustic input to the hearing aid. This is generally called “noise”. This will be the subject of Part II of this issue. The first part of this issue discusses the causes and effect of distortion. First, different types of distortion are described, followed by an explanation of how they are measured. This is followed by a discussion of the sources of distortion that may be present in hearing aids and the various mechanisms by which distortion is created. The final section of Part I discusses the effects of distortion on the hearing aid wearer. For the reader having difficulty understanding the technical concepts in the first part of this tutorial, a good overview from a different perspective has been presented by Kuk (1996). The second part of this issue discusses the causes and effects of internal noise in hearing aids. This part starts with a discussion of sources of internal noise and continues with a description of methods for the measurement of internal noise. This part concludes with a discussion of the perception of internal noise and its effects on the user of hearing aids. At the end of the text is an intentionally long list of references, which is intended to serve as a reasonably comprehensive resource for the reader seeking further information on distortion and noise in hearing aids.

Strategy and implementing techniques for the sound quality target of car interior noise during acceleration

Affine projection algorithms (APA) have been widely employed for acoustic echo cancellation (AEC) since they provide a natural trade-off between convergence speed and computational complexity. However, their application in Acoustic Feedback Cancellation (AFC) in hearing aids so far has been limited due to lack of performance improvement in one microphone settings. A two microphone technique was recently proposed to provide an improved cancellation for a larger class of input signals. This paper proposes to use APA in the two microphone closed-loop feedback cancellation. It is shown that APA has significantly improved the misalignment and maximum stable gain of the system. Moreover, a new variable Gaussian step-size control (VGSS) for APA is also proposed. The simulation results indicate an improvement in convergence speed of the proposed algorithms as compared to previously suggested methods.

This paper presents a hybrid active noise cancelling (HANC) algorithm with online secondary path estimation, together with its evaluation under acoustic feedback distortion present in most feedforward ANC system. The HANC system provides a suitable solution to two important problems present in most ANC systems. The acoustic feedback is reduced using two FIR adaptive filters with feedforward and feedback configurations, respectively; together with the online secondary path modeling. Computer simulation results show that the HANC structure provides a good acoustic feedback cancellation, while the secondary path estimation method performs fairly well, providing better cancelation performance than other previously proposed structures.

This paper presents the correlation between psychological and physiological acoustics for the automotive sound. The research purpose of this paper is to evaluate the sound quality of interior sound of a passenger car based human sensibility. The conventional method for the objective evaluation of sound quality is to use the only sound metrics based on psychological acoustics. This method used not only psychological acoustics, but also physiological acoustics. For this work, the sounds of five premium passenger cars are used for the subjective evaluation. The correlation between this subjective rating and sound metrics based on psychological acoustics is calculated. Finally, the correlated sound metric is used for calculating the correlation between sound metric and the electron cephalogram signal measured on the brain. Throughout these results, the new evaluation system for the sound quality on interior sound of a passenger car has been developed.

The improvement of social economy has promoted the vigorous development of the automobile industry, more and more people have their own special vehicles-cars, and put forward higher requirements for the appearance, comfort and safety of cars. In traffic accidents, rear-end collisions occur from time to time. Although the fatality rate is relatively low, it is easy to cause neck injuries to the occupants. Therefore, besides driver seat whipping (Whiplash), the second row seat whipping test is introduced into the system for the first time in the 2021 version of C-NCAP evaluation system. For the seat, according to the test results of the 2021 edition C-NCAP evaluation system, the finite element whipping alignment CAE model of the second row independent seat of a passenger car is established, and the calculation results of the whipping simulation model are obtained, in which the poor NIC, Upper Fz and Upper My are close to the test results. At the same time, the seat improvement scheme is proposed for the deduction items NIC, Upper Fz and Upper My, and the simulation verification of the improved second row seats is carried out. The results show that the Upper Fz can be improved by optimizing the effective height of the headrest, and the NIC and Upper My can be effectively improved by improving the frame stiffness of the headrest area. The final simulation results meet the requirements of the second row seat whipping score of the car, and provide theoretical and experimental basis for the optimization analysis of the second row seat.

Acoustic Feedback Cancellation in Hearing Aids Exploiting an Inertial Sensor

We propose a combination of the well known generalized sidelobe canceller (GSC) or Griffiths-Jim beamformer, and the so-called PEM-AFROW algorithm for closed loop room impulse response estimation, resulting in a system for multimicrophone proactive acoustic feedback cancellation. For public address applications in low-reverberant environments, the computational complexity is reduced dramatically compared to state of the art proactive acoustic feedback cancellers, while performance is only marginally degraded.

Publication in the conference proceedings of EUSIPCO, Bucharest, Romania, 2012