Predictions of formant-frequency discrimination in noise based on model auditory-nerve responses.
To better understand how the auditory system extracts speech signals in the presence of noise, discrimination thresholds for the second formant frequency were predicted with simulations of auditory-nerve responses. These predictions employed either average-rate information or combined rate and timing information, and either populations of model fibers tuned across a wide range of frequencies or a subset of fibers tuned to a restricted frequency range. In general, combined temporal and rate information for a small population of model fibers tuned near the formant frequency was most successful in replicating the trends reported in behavioral data for formant-frequency discrimination. To explore the nature of the temporal information that contributed to these results, predictions based on model auditory-nerve responses were compared to predictions based on the average rates of a population of cross-frequency coincidence detectors. These comparisons suggested that average response rate (count) of cross-frequency coincidence detectors did not effectively extract important temporal information from the auditory-nerve population response. Thus, the relative timing of action potentials across auditory-nerve fibers tuned to different frequencies was not the aspect of the temporal information that produced the trends in formant-frequency discrimination thresholds.
Tan
Qing
Q
Boston University Hearing Research Center, Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, Massachusetts 02215, USA.
Carney
Laurel H
LH
D000161:Acoustic Stimulation; D001309:Auditory Threshold / Q000502:physiology*; D003056:Cochlear Nerve / Q000502:physiology*; D004192:Discrimination, Psychological / Q000502:physiology; D006801:Humans; D008954:Models, Biological; D009622:Noise; D010700:Phonetics; D011237:Predictive Value of Tests; D013061:Speech Acoustics; D013067:Speech Perception / Q000502:physiology*