No abstract

Background A model that can accurately predict speech intelligibility for a given hearing-impaired (HI) listener would be an important tool for hearing-aid fitting or hearing-aid algorithm development. Existing speech-intelligibility models do not incorporate variability in suprathreshold deficits that are not well predicted by classical audiometric measures. One possible approach to the incorporation of such deficits is to base intelligibility predictions on sensitivity to simultaneously spectrally and temporally modulated signals. Purpose The likelihood of success of this approach was evaluated by comparing estimates of spectrotemporal modulation (STM) sensitivity to speech intelligibility and to psychoacoustic estimates of frequency selectivity and temporal fine-structure (TFS) sensitivity across a group of HI listeners. Research Design The minimum modulation depth required to detect STM applied to an 86 dB SPL four-octave noise carrier was measured for combinations of temporal modulation rate (4, 12, or 32 Hz) and spectral modulation density (0.5, 1, 2, or 4 cycles/octave). STM sensitivity estimates for individual HI listeners were compared to estimates of frequency selectivity (measured using the notched-noise method at 500, 1000measured using the notched-noise method at 500, 2000, and 4000 Hz), TFS processing ability (2 Hz frequency-modulation detection thresholds for 500, 10002 Hz frequency-modulation detection thresholds for 500, 2000, and 4000 Hz carriers) and sentence intelligibility in noise (at a 0 dB signal-to-noise ratio) that were measured for the same listeners in a separate study. Study Sample Eight normal-hearing (NH) listeners and 12 listeners with a diagnosis of bilateral sensorineural hearing loss participated. Data Collection and Analysis STM sensitivity was compared between NH and HI listener groups using a repeated-measures analysis of variance. A stepwise regression analysis compared STM sensitivity for individual HI listeners to audiometric thresholds, age, and measures of frequency selectivity and TFS processing ability. A second stepwise regression analysis compared speech intelligibility to STM sensitivity and the audiogram-based Speech Intelligibility Index. Results STM detection thresholds were elevated for the HI listeners, but only for low rates and high densities. STM sensitivity for individual HI listeners was well predicted by a combination of estimates of frequency selectivity at 4000 Hz and TFS sensitivity at 500 Hz but was unrelated to audiometric thresholds. STM sensitivity accounted for an additional 40% of the variance in speech intelligibility beyond the 40% accounted for by the audibility-based Speech Intelligibility Index. Conclusions Impaired STM sensitivity likely results from a combination of a reduced ability to resolve spectral peaks and a reduced ability to use TFS information to follow spectral-peak movements. Combining STM sensitivity estimates with audiometric threshold measures for individual HI listeners provided a more accurate prediction of s...

Normal-hearing and hearing-impaired listeners were tested to determine F0 difference limens for synthetic tokens of 5 steady-state vowels. The same stimuli were then used in a concurrent-vowel labeling task with the F0 difference between concurrent vowels ranging between 0 and 4 semitones. Finally, speech recognition was tested for synthetic sentences in the presence of a competing synthetic voice with the same, a higher, or a lower F0. Normal-hearing listeners and hearing-impaired listeners with small F0-discrimination (deltaF0) thresholds showed improvements in vowel labeling when there were differences in F0 between vowels on the concurrent-vowel task. Impaired listeners with high deltaF0 thresholds did not benefit from F0 differences between vowels. At the group level, normal-hearing listeners benefited more than hearing-impaired listeners from F0 differences between competing signals on both the concurrent-vowel and sentence tasks. However, for individual listeners, deltaF0 thresholds and improvements in concurrent-vowel labeling based on F0 differences were only weakly associated with F0-based improvements in performance on the sentence task. For both the concurrent-vowel and sentence tasks, there was evidence that the ability to benefit from F0 differences between competing signals decreases with age.

Abstract-Thirty-six blast-exposed patients and twenty-nine non-blast-exposed control subjects were tested on a battery of behavioral and electrophysiological tests that have been shown to be sensitive to central auditory processing deficits. Abnormal performance among the blast-exposed patients was assessed with reference to normative values established as the mean performance on each test by the control subjects plus or minus two standard deviations. Blast-exposed patients performed abnormally at rates significantly above that which would occur by chance on three of the behavioral tests of central auditory processing: the Gaps-In-Noise, Masking Level Difference, and Staggered Spondaic Words tests. The proportion of blast-exposed patients performing abnormally on a speech-in-noise test (Quick Speech-In-Noise) was also significantly above that expected by chance. These results suggest that, for some patients, blast exposure may lead to difficulties with hearing in complex auditory environments, even when peripheral hearing sensitivity is near normal limits.Key words: audiometric evaluation, auditory dysfunction, auditory processing disorder, blast, central auditory processing, evoked potential, hearing loss, rehabilitation, traumatic brain injury, Veterans. INTRODUCTION The recent conflicts in Afghanistan and

Because adaptive tracking procedures are designed to avoid stimulus levels far from a target threshold value, the psychometric function constructed from the trial-by-trial data in the track may be accurate near the target level but a poor reflection of performance at levels far removed from the target. A series of computer simulations was undertaken to assess the reliability and accuracy of psychometric functions generated from data collected in up-down adaptive tracking procedures. Estimates of psychometric function slopes were obtained from trial-by-trial data in simulated adaptive tracks and compared with the true characteristics of the functions used to generate the tracks. Simulations were carried out for three psychophysical procedures and two target performance levels, with tracks generated by psychometric functions with three different slopes. The functions reconstructed from the tracking data were, for the most part, accurate reflections ofthe true generating functions when at least 200 trials were included in the tracks. However, for 50-and 100-trial tracks, slope estimates were biased high for all simulated experimental conditions. Correction factors for slope estimates from these tracks are presented. There was no difference in the accuracy and reliability of slope estimation due to target level for the adaptive track, and only minor differences due to psychophysical procedure. It is recommended that, ifboth threshold and slope of psychometric functions are to be estimated from the trial-by-trial tracking data, at least 100 trials should be included in the tracks, and a three-or four-alternative forced-choice procedure should be used. However, good estimates can also be obtained using the two-alternative forced-choice procedure or less than 100 trials if appropriate corrections for bias are applied.Adaptive testing procedures have become popular in psychophysical experiments over the past 20 years due to their efficiency and speed. In these procedures, the level of a stimulus on each experimental trial is determined by performance on previous trials. Such methods are characterized by their ability to converge rapidly on a given level of performance and to concentrate experimental trials in the vicinity of the final measurement of interest. Little experimental time and subject energy is expended on trials placed far from the point of interest on the psychometric function.The trade for this high efficiency, however, is the loss of information about the underlying function that defines