This paper presents an index designed to predict music quality for individuals listening through hearing aids. The index is "intrusive", that is, it compares the degraded signal being evaluated to a reference signal. The index is based on a model of the auditory periphery that includes the effects of hearing loss. Outputs from the auditory model are used to measure changes in the signal time-frequency envelope modulation, temporal fine structure, and long-term spectrum caused by the hearing aid processing. The index is constructed by combining a term sensitive to noise and nonlinear distortion with a second term sensitive to changes in the long-term spectrum. The index is fitted to an existing database of music quality judgments made by listeners having normal or impaired hearing. The data comprise ratings for three music excerpts (classical orchestra, jazz trio, and jazz singer), each processed through 100 conditions representative of hearing-aid processing and listening situations. The overall accuracy of the index is high, with a correlation coefficient of 0.970 when computed over all of the processing conditions and averaged over the combined groups of listeners having normal and impaired hearing.

Speech quality metrics are used to predict quality under a variety of noise and distortion conditions. A simple metric for noisy speech is the signal-to-noise ratio (SNR), which gives the ratio of the long-term average speech power to the long-term average noise power. However, the average noise level fails to include the impact of the noise amplitude modulation on speech quality judgments. This paper reviews how the noise characteristics affect quality ratings even when the SNR is held constant. In one study, ratings for speech combined with stationary Gaussian noise are compared to ratings for noise having the same envelope modulation as the speech. In a second study, ratings for speech combined with continuous noise or multi-talker babble are compared to speech where the interference is gated off during the silent intervals in the stimulus. An accurate quality metric must take into account the modulation as well as the intensity of the noise, and the implications for speech quality metrics are discussed.

A probabilistic kernel approach to pairwise preference learning based on Gaussian processes is applied to predict preference judgments for sound quality degradation mechanisms that might be present in a hearing aid. Subjective sound quality comparisons for 14 normal-hearing and 18 hearing-impaired subjects were used for evaluating the predictive performance. 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 kernel approach gives a significant improvement in preference predictions of hearing-impaired subjects by individualizing the learning process. A significant difference is shown between normal-hearing and hearing-impaired subjects, because of nonlinearities in the perception of hearing-impaired subjects. In particular, hearing-impaired subjects have significant nonlinear preference judgments when making pairwise comparisons between peak clipped sentences with different clipping thresholds. The probabilistic kernel approach is shown to be robust when generalizing over distortions and over subjects.

Two-tone rate suppression is a nonlinear property of the cochlea in which the total neural firing rate in the region most sensitive to a probe tone is reduced by the addition of a second (suppressor) tone at a different frequency. A cochlear model featuring a cascade of adaptive-Q filter sections was investigated to determine its ability to reproduce two-tone suppression. It was found that the adaptive-Q filter sections are adequate to reproduce two-tone suppression when the suppressor is located higher in frequency than the probe tone but are not adequate to reproduce suppression for a suppressor lower in frequency than the probe. A modification to the cochlear model, in which the output signal level is adjusted in response to the estimated peak signal levels in the regions of the cochlear filter tip and tail, was much more accurate in reproducing two-tone suppression behavior. A speech example is also presented, and the implications of two-tone suppression in applications of the cochlear model are discussed.>

Most practical models of cochlear mechanics are based on approximations to the wave equation in the cochlea. These approximations engender compromises in the accuracy with which the cochlear motion can be reproduced. Tuning curves are compared here for two cochlear models, one based on a cascade of low-pass filter sections and the other based on a cascade of filter sections derived from a one-dimensional transmission line. The filters in the two simulations are designed to give comparable latency in the neural response to inputs at different frequencies, and the simulations include an active gain-control mechanism to adjust the characteristics of each section with changes in the input signal level. The resultant simulated tuning curves and neural outputs indicate that the modified transmission-line approximation yields a more accurate cochlear model.>

An adaptive digital time-domain model of the human cochlea is presented. The model consists of the middle ear, the mechanical motion of the cochlea, and the neural transconduction 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 modeled by a second filter that sharpens the excitation to the inner hair cell. The 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.>

Feedback cancellation in hearing aids is discussed. It involves estimating the feedback signal and subtracting it from the microphone input signal. The system described updates the estimated feedback path whenever changes are detected in the feedback behavior. The normal hearing-aid processing is then interrupted, a probe signal is injected into the system, and a set of filter coefficients is adjusted to give an estimate and the feedback path. Both LMS adaptive filter and Wiener filter approaches were simulated, with the Wiener filter giving better performance at poor signal-to-noise ratios. The simulation results indicate that feedback suppression in excess of 10 dB is possible.>

Many techniques have been proposed for the high-resolution processing of an array having an arbitrary geometry. We show that many high-resolution techniques can be represented using a common formulation based on the eigenvectors and eigenvalues of the correlation matrix. This formulation suggests a family of high-resolution spectral estimators governed by a single parameter that can be selected to give continuous adjustment of the spectral resolution. Setting the resolution parameter also affects the bearing-estimation accuracy, and we investigate the trade-off between resolution and accuracy using a simulated two-dimensional array.

Modern array processor and digital signal processing technologies have been applied to develop a real-time, software-based system that simulates high-frequency (HF) radio links. This system is called an HF Channel Simulator. In this paper we describe the design features and performance of one such simulator, based on the Floating Point Systems AP-120B array processor. The simulator characteristics are a 4 kHz signal bandwidth and a great flexibility in the selection of link parameters available to the user. All distortions are at least 50 dB below the desired signal output level.

Constant-Q spectral analysis can be performed by taking the Fourier transform of a windowed sequence where the window is a function of the product of time and frequency. If the window used is a decaying exponential whose argument is a constant times the product of time and frequency, the result is equivalent to evaluating the z-transform of the sequence along an outwardly going spiral in the complex z-plane. This analysis can thus be implemented using the chirp z-transform algorithm, and is discussed for the specific case of loudspeaker impulse-response measurements.