A study of detection models for narrowband reproducible noise
Binaural hearing studies focus on how binaural processing improves the extraction of information from one source in the presence of competing sources. The most extensively studied condition is the detection of an out-of-phase tonal signal in an interaurally identical, Gaussian masking noise, called the N0Spi condition. Recently, attention turned to the dependence of detection performance on individual waveforms in the context of random noise waveforms from trial to trial. This thesis addresses this dependence, as measured in experiments (Isabelle 1991, 1995) that estimated probabilities of detection (Pd) and false alarm (Pf) for each of 30, narrowband-noise waveforms in the N0Spi condition. In previous work, models were shown to describe average performance and much of the variation over Pd, but the variation of Pf across noise samples was not explained. The current study explores two approaches to understanding the variation of Pd and Pf with noise waveform. First, a metric based on Shannon entropy is evaluated with the entropy computed from a combination of Pd and Pf. Second, internal noise in the form of temporal jitter is incorporated into existing interaural differences models. Results show that the correlation of the variation of interaural differences with the entropy is slightly stronger than that correlation with Pd alone. Models based on variations in the interaural differences with temporal jitter included are neither better nor worse than those without temporal jitter. Overall, these results suggest that the variation with Pf as captured by the entropy can be explained by interaural difference models.
Thesis (M.Sc.Eng.) PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at email@example.com. Thank you.