Relating the variability of tone-burst otoacoustic emission and auditory brainstem response latencies to the underlying cochlear mechanics

Forward and reverse cochlear latency and its relation to the frequency tuning of the auditory filters can be assessed using tone bursts (TBs). Otoacoustic emissions (TBOAEs) estimate the cochlear roundtrip time, while auditory brainstem responses (ABRs) to the same stimuli aim at measuring the auditory filter buildup time. Latency ratios are generally close to two and controversy exists about the relationship of this ratio to cochlear mechanics. We explored why the two methods provide different estimates of filter buildup time, and ratios with large inter-subject variability, using a time-domain model for OAEs and ABRs. We compared latencies for twenty models, in which all parameters but the cochlear irregularities responsible for reflection-source OAEs were identical, and found that TBOAE latencies were much more variable than ABR latencies. Multiple reflection-sources generated within the evoking stimulus bandwidth were found to shape the TBOAE envelope and complicate the interpretation of TBOAE latency and TBOAE/ABR ratios in terms of auditory filter tuning

Estimation of auditory filter shapes across frequencies using machine learning

When fitting a hearing aid, the level-dependent gain prescribed at each frequency is usually based on the hearing loss at that frequency. This often results in reasonable fittings for a typical cochlear hearing loss, but may fail when the individual frequency selectivity and/or loudness growth are different from what would be typical for that hearing loss. Individualised fitting based on measures of frequency selectivity might be useful in improving a fitting, for example by reducing across-channel masking. A popular measure of frequency selectivity is the notched-noise method, but this test is time-consuming. To reduce testing time, Shen and Richards (2013) proposed an efficient machine-learning test that determines the slope of the skirts of the auditory filter (p), its minimum response for wide notches (r), and detection efficiency (K). However, their test did not determine asymmetries in the auditory filter, which are important to consider during fitting to reduce across-channel masking. The test proposed here provides a time-efficient way of estimating the auditory filter shape and asymmetry as a function of center frequency. The noise level required for threshold is estimated for a tone with frequency fs presented at 15 dB SL in nine symmetric or asymmetric notched noises with notch edge frequencies between 0.6 and 1.4 fs. Using only narrow to medium notch widths provides good information about the tip of the auditory filter, which is of most importance in determining across-channel masking for speech-like signals (but the tail is not well defined). The nine thresholds for a given fs can be used to fit an auditory filter model with three parameters: the slopes of the lower and upper sides (pl, pu) and K. In practice, these model parameters are estimated as a continuous function of fs, and fs is varied across trials over the range 0.5-4 kHz. The stimulus parameters on a given trial (fs, notch condition, noise level) are chosen to maximally reduce the uncertainty in the model parameters, exploiting the covariance between thresholds for adjacent values of fs. Six subjects have been tested so far. The whole procedure took about 45 minutes per ear. The lower slopes typically corresponded with values expected from the audiogram and a cochlear hearing loss. The upper slopes were steeper in some cases, although not necessarily across the whole frequency range. Reference Shen, Y., and Richards, V. M. (2013). "Bayesian adaptive estimation of the auditory filter," J. Acoust. Soc. Am. 134, 1134-1145.EPSR

Automatic wheeze detection based on auditory modelling

Automatic wheeze detection has several potential benefits compared with reliance on human auscultation: it is experience independent, an automated historical record can easily be kept, and it allows quantification of wheeze severity. Previous attempts to detect wheezes automatically have had partial success but have not been reliable enough to become widely accepted as a useful tool. In this paper an improved algorithm for automatic wheeze detection based on auditory modelling is developed, called the frequency- and duration-dependent threshold algorithm. The mean frequency and duration of each wheeze component are obtained automatically. The detected wheezes are marked on a spectrogram. In the new algorithm, the concept of a frequency- and duration-dependent threshold for wheeze detection is introduced. Another departure from previous work is that the threshold is based not on global power but on power corresponding to a particular frequency range. The algorithm has been tested on 36 subjects, 11 of whom exhibited characteristics of wheeze. The results show a marked improvement in the accuracy of wheeze detection when compared with previous algorithms

Room reflections and constancy in speech-like sounds: within-band effects

The experiment asks whether constancy in hearing precedes or follows grouping. Listeners heard speech-like sounds comprising 8 auditory-filter shaped noise-bands that had temporal envelopes corresponding to those arising in these filters when a speech message is played. The „context‟ words in the message were “next you‟ll get _to click on”, into which a “sir” or “stir” test word was inserted. These test words were from an 11-step continuum that was formed by amplitude modulation. Listeners identified the test words appropriately and quite consistently, even though they had the „robotic‟ quality typical of this type of 8-band speech. The speech-like effects of these sounds appears to be a consequence of auditory grouping. Constancy was assessed by comparing the influence of room reflections on the test word across conditions where the context had either the same level of reflections, or where it had a much lower level. Constancy effects were obtained with these 8-band sounds, but only in „matched‟ conditions, where the room reflections were in the same bands in both the context and the test word. This was not the case in a comparison „mismatched‟ condition, and here, no constancy effects were found. It would appear that this type of constancy in hearing precedes the across-channel grouping whose effects are so apparent in these sounds. This result is discussed in terms of the ubiquity of grouping across different levels of representation

Frame Theory for Signal Processing in Psychoacoustics

This review chapter aims to strengthen the link between frame theory and signal processing tasks in psychoacoustics. On the one side, the basic concepts of frame theory are presented and some proofs are provided to explain those concepts in some detail. The goal is to reveal to hearing scientists how this mathematical theory could be relevant for their research. In particular, we focus on frame theory in a filter bank approach, which is probably the most relevant view-point for audio signal processing. On the other side, basic psychoacoustic concepts are presented to stimulate mathematicians to apply their knowledge in this field

An investigation into the efficacy of methods commonly employed by mix engineers to reduce frequency masking in the mixing of multitrack musical recordings

Studio engineers use a variety of techniques to reduce frequency masking between instruments when mixing multi-track musical recordings. This study evaluates the efficacy of three techniques, namely mirrored equalization, frequency spectrum sharing and stereo panning, against their variations to confirm the veracity of accepted practice. Mirrored equalisation involves boosting one instrument and cutting the other at the same frequency. Frequency spectrum sharing involves low pass filtering one instrument and high pass filtering the other. Panning involves placing two competing instruments at different pan positions. Test subjects used eight tools comprising a single unlabeled slider to reduce frequency masking in several two instrument scenarios. Satisfaction values were recorded. Results indicate subjects preferred using tools that panned both audio tracks