Electrical and Electronic Engineering - Research Publications

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Author: Blamey, Peter × Author: Burkitt, Anthony × Author: Erfanian Saeedi, Nafise × End date: 2016 × Start date: 2010 × Type: Journal Article ×

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    Learning Pitch with STDP: A Computational Model of Place and Temporal Pitch Perception Using Spiking Neural Networks
    Saeedi, NE ; Blamey, PJ ; Burkitt, AN ; Grayden, DB ; Battaglia, FP (PUBLIC LIBRARY SCIENCE, 2016-04)
    Pitch perception is important for understanding speech prosody, music perception, recognizing tones in tonal languages, and perceiving speech in noisy environments. The two principal pitch perception theories consider the place of maximum neural excitation along the auditory nerve and the temporal pattern of the auditory neurons' action potentials (spikes) as pitch cues. This paper describes a biophysical mechanism by which fine-structure temporal information can be extracted from the spikes generated at the auditory periphery. Deriving meaningful pitch-related information from spike times requires neural structures specialized in capturing synchronous or correlated activity from amongst neural events. The emergence of such pitch-processing neural mechanisms is described through a computational model of auditory processing. Simulation results show that a correlation-based, unsupervised, spike-based form of Hebbian learning can explain the development of neural structures required for recognizing the pitch of simple and complex tones, with or without the fundamental frequency. The temporal code is robust to variations in the spectral shape of the signal and thus can explain the phenomenon of pitch constancy.
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    Application of a pitch perception model to investigate the effect of stimulation field spread on the pitch ranking abilities of cochlear implant recipients
    Saeedi, NE ; Blamey, PJ ; Burkitt, AN ; Grayden, DB (ELSEVIER SCIENCE BV, 2014-10)
    Although many cochlear implant (CI) recipients perceive speech very well in favorable conditions, they still have difficulty with music, speech in noisy environments, and tonal languages. Studies show that CI users' performance in these tasks are correlated with their ability to perceive pitch. The spread of stimulation field from the electrodes to the auditory nerve is one of the factors affecting performance. This study proposes a model of auditory perception to predict the performance of CI users in pitch ranking tasks using an existing sound processing scheme. The model is then used as a platform to investigate the effect of stimulation field spread on performance.