James M. Kates

Coherence and the Speech Intelligibility Index

The speech intelligibility index (SII) (ANSI S3.5-1997) provides a means for estimating speech intelligibility under conditions of additive stationary noise or bandwidth reduction. The SII concept for estimating intelligibility is extended in this paper to include broadband peak-clipping and center-clipping distortion, with the coherence between the input and output signals used to estimate the noise and distortion effects. The speech intelligibility predictions using the new procedure are compared with intelligibility scores obtained from normal-hearing and hearing-impaired subjects for conditions of additive noise and peak-clipping and center-clipping distortion. The most effective procedure divides the speech signal into low-, mid-, and high-level regions, computes the coherence SII separately for the signal segments in each region, and then estimates intelligibility from a weighted combination of the three coherence SII values.

Feedback cancellation in hearing aids: results from a computer simulation

Feedback cancellation in hearing aids involves estimating the feedback signal and subtracting it from the microphone input signal. The feedback-cancellation system described updates the estimated feedback path whenever changes are detected in the feedback behavior. When a change is detected, the normal hearing-aid processing is interrupted, a pseudorandom probe signal is injected into the system, and a set of filter coefficients is adjusted to give an estimate of the feedback path. The hearing aid is then returned to normal operation with the feedback-cancellation filter as part of the system. Two approaches are investigated for computing the filter coefficients: a least-mean square (LMS) adaptive filter and a Wiener filter. Test results are presented for a computer simulation of an in-the-ear (ITE) hearing aid. The simulation results indicate that more than 10 dB of cancellation can be obtained and that the Wiener filter is more effective in the presence of strong interference. >

A time-domain digital cochlear model

The author presents a digital time-domain model of the human cochlea designed to represent normal auditory functioning and to allow for degradation related to auditory impairment. The model consists of the middle ear, the mechanical motion of the cochlea, and the neural transduction of the inner hair cells. The traveling waves on the cochlear partition are represented by a cascade of digital filter sections, and the cochlear micromechanics are represented by a second filter that further sharpens the excitation to the inner hair cells. The neural firing rate is determined by the sum of the outputs of multiple fibers attached to each inner hair cell, with the fiber neurons having firing characteristics representative of low- and high-spontaneous-rate fibers. The signal processing cochlear model incorporates dynamic-range compression by adjusting the Q of each cochlear filter section and second filter in response to the second-filter velocity and the averaged neural firing rate. Examples of the model response to impulse and tone-burst stimuli and to synthetic speech are presented. >

A comparison of hearing‐aid array‐processing techniques

Microphone arrays have proven effective in improving speech intelligibility in noise for hearing-impaired listeners, and several array processing techniques have been proposed for hearing aids. Among the signal-processing approaches are classical delay-and-sum beamforming, superdirective arrays, and adaptive arrays. To directly compare the effectiveness of these different processing strategies, a 10-cm-long linear array was built using five uniformly spaced omnidirectional microphones. This array was used in the end-fire orientation to acquire speech and noise signals for a variety of array placements in two representative rooms. Both digital and simulated analog processing techniques were considered, with the array processing implemented in the frequency domain. The performance metric was the steady-state array gain weighted to represent the relative importance of the different frequency regions in understanding speech. The processing comparison indicates that digital systems are more effective than the simulated analog processing, and that both superdirective and adaptive digital array processing can provide more than 9 dB of weighted array gain.

Constrained adaptation for feedback cancellation in hearing aids

In feedback cancellation in hearing aids, an adaptive filter is used to model the feedback path. The output of the adaptive filter is subtracted from the microphone signal to cancel the acoustic and mechanical feedback picked up by the microphone, thus allowing more gain in the hearing aid. In general, the feedback-cancellation filter adapts on the hearing-aid input signal, and signal cancellation and coloration artifacts can occur for a narrow-band input. In this paper, two procedures for LMS adaptation with a constraint on the magnitude of the adaptive weight vector are derived. The constraints greatly reduce the probability that the adaptive filter will cancel a narrow-band input. Simulation results are used to demonstrate the efficacy of the constrained adaptation.

Working memory, age, and hearing loss: susceptibility to hearing aid distortion.

Objectives: Hearing aids use complex processing intended to improve speech recognition. Although many listeners benefit from such processing, it can also introduce distortion that offsets or cancels intended benefits for some individuals. The purpose of the present study was to determine the effects of cognitive ability (working memory) on individual listeners’ responses to distortion caused by frequency compression applied to noisy speech. Design: The present study analyzed a large data set of intelligibility scores for frequency-compressed speech presented in quiet and at a range of signal-to-babble ratios. The intelligibility data set was based on scores from 26 adults with hearing loss with ages ranging from 62 to 92 years. The listeners were grouped based on working memory ability. The amount of signal modification (distortion) caused by frequency compression and noise was measured using a sound quality metric. Analysis of variance and hierarchical linear modeling were used to identify meaningful differences between subject groups as a function of signal distortion caused by frequency compression and noise. Results: Working memory was a significant factor in listeners’ intelligibility of sentences presented in babble noise and processed with frequency compression based on sinusoidal modeling. At maximum signal modification (caused by both frequency compression and babble noise), the factor of working memory (when controlling for age and hearing loss) accounted for 29.3% of the variance in intelligibility scores. Combining working memory, age, and hearing loss accounted for a total of 47.5% of the variability in intelligibility scores. Furthermore, as the total amount of signal distortion increased, listeners with higher working memory performed better on the intelligibility task than listeners with lower working memory did. Conclusions: Working memory is a significant factor in listeners’ responses to total signal distortion caused by cumulative effects of babble noise and frequency compression implemented with sinusoidal modeling. These results, together with other studies focused on wide-dynamic range compression, suggest that older listeners with hearing loss and poor working memory are more susceptible to distortions caused by at least some types of hearing aid signal-processing algorithms and by noise, and that this increased susceptibility should be considered in the hearing aid fitting process.

Superdirective arrays for hearing aids

Microphone arrays are the most effective of the techniques that have been proposed for improving speech intelligibility in noise for the hearing impaired. However, classical delay‐and‐sum beamforming provides very small amounts of array gain at low frequencies, while adaptive array processing has been shown to cancel the desired signal in the presence of strong room reflections. Superdirective arrays offer a heretofore overlooked solution in which optimal performance can be obtained for a stationary random noise field, but where the desired signal will not be canceled. A short constrained superdirective array suitable for hearing‐aid applications is proposed in this paper, and its theoretical performance is evaluated.

On using coherence to measure distortion in hearing aids

Coherence is a frequency-domain measure of the degree to which the output of a system is linearly related to the system input. The signal-to-distortion ratio (SDR), where the distortion term includes all nonlinear effects and noise in the system, can be computed from the coherence. The coherence estimate, however, is subject to sources of variance and bias that reduce the accuracy of the measured SDR. The origins of the variance and bias and their effects on distortion measurements are presented. New procedures for reducing the variance and bias effects are described, and the processing effectiveness is demonstrated for a simulated hearing-aid response.

Classification of background noises for hearing‐aid applications

A background-noise classification procedure is being developed for hearing-aid applications, wherein the hearing-aid response would be adjusted in response to changes in the noise environment. The classification procedure is based on measuring four signal features giving the fluctuations of the signal envelope and the mean frequency and low- and high-frequency slopes of the average spectrum. A more complicated procedure, based on determining the envelope modulation spectra in auditory critical bands, was also investigated and was found to offer no advantages over the simpler procedure. The accuracy of the classification procedure was determined for eleven everyday background noises under optimal conditions where the training and test noise sequences were different portions of the same short noise recording. A cluster analysis was used to determine the similarities among the feature vectors for the noises, and when the noises are grouped into a reduced number of clusters the noise-classification accuracy using the four features exceeds 90%.

Effects of noise and distortion on speech quality judgments in normal-hearing and hearing-impaired listeners.

Noise and distortion reduce speech intelligibility and quality in audio devices such as hearing aids. This study investigates the perception and prediction of sound quality by both normal-hearing and hearing-impaired subjects for conditions of noise and distortion related to those found in hearing aids. Stimuli were sentences subjected to three kinds of distortion (additive noise, peak clipping, and center clipping), with eight levels of degradation for each distortion type. The subjects performed paired comparisons for all possible pairs of 24 conditions. A one-dimensional coherence-based metric was used to analyze the quality judgments. This metric was an extension of a speech intelligibility metric presented in Kates and Arehart (2005) [J. Acoust. Soc. Am. 117, 2224-2237] and is based on dividing the speech signal into three amplitude regions, computing the coherence for each region, and then combining the three coherence values across frequency in a calculation based on the speech intelligibility index. The one-dimensional metric accurately predicted the quality judgments of normal-hearing listeners and listeners with mild-to-moderate hearing loss, although some systematic errors were present. A multidimensional analysis indicates that several dimensions are needed to describe the factors used by subjects to judge the effects of the three distortion types.