title: Effects of Physiological Internal Noise on Model Predictions of Concurrent Vowel Identification for Normal-Hearing Listeners.
abstract: Previous studies have shown that concurrent vowel identification improves with increasing temporal onset asynchrony of the vowels, even if the vowels have the same fundamental frequency. The current study investigated the possible underlying neural processing involved in concurrent vowel perception. The individual vowel stimuli from a previously published study were used as inputs for a phenomenological auditory-nerve (AN) model. Spectrotemporal representations of simulated neural excitation patterns were constructed (i.e., neurograms) and then matched quantitatively with the neurograms of the single vowels using the Neurogram Similarity Index Measure (NSIM). A novel computational decision model was used to predict concurrent vowel identification. To facilitate optimum matches between the model predictions and the behavioral human data, internal noise was added at either neurogram generation or neurogram matching using the NSIM procedure. The best fit to the behavioral data was achieved with a signal-to-noise ratio (SNR) of 8 dB for internal noise added at the neurogram but with a much smaller amount of internal noise (SNR of 60 dB) for internal noise added at the level of the NSIM computations. The results suggest that accurate modeling of concurrent vowel data from listeners with normal hearing may partly depend on internal noise and where internal noise is hypothesized to occur during the concurrent vowel identification process.
authors: Department of Audiology and Speech Pathology, University of Tennessee Health Science Center, Knoxville, TN, United States of America.
authors: Mark S
authors: MS
authors: Hedrick
authors: Department of Otorhinolaryngology-Head and Neck Surgery, Samsung Medical Center, Sungkyunkwan University, School of Medicine, Seoul, Korea.
authors: Il Joon
authors: IJ
authors: Moon
authors: Department of Biomedical Engineering, University of Ulsan, Ulsan, Korea.
authors: Jihwan
authors: J
authors: Woo
authors: Department of Audiology and Speech Pathology, University of Tennessee Health Science Center, Knoxville, TN, United States of America.
authors: Jong Ho
authors: JH
authors: Won
mesh_terms: D000328:Adult; D000465:Algorithms; D001307:Auditory Perception; D001309:Auditory Threshold / Q000502:physiology*; D003056:Cochlear Nerve / Q000503:physiopathology; D003198:Computer Simulation; D005260:Female; D006309:Hearing; D006801:Humans; D008297:Male; D009474:Neurons / Q000502:physiology; D009622:Noise; D010700:Phonetics; D059629:Signal-To-Noise Ratio; D013063:Speech Discrimination Tests; D013067:Speech Perception; D055815:Young Adult