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After March 20202020MarchFebruaryJanuary2019DecemberNovemberOctoberSeptemberAugustJulyJuneMayAprilMarchFebruaryJanuary2018DecemberNovemberOctoberSeptemberAugustJulyJuneMayAprilMarchFebruaryJanuary2017DecemberNovemberOctoberSeptemberAugustJulyJuneMayAprilMarchFebruaryJanuary2016DecemberNovemberOctoberSeptemberAugustJulyJuneMayAprilBefore April 2016 |
Schedule in January 2017The 32nd Perceptual Frontier Seminar: How to Measure Capacities of the Auditory SystemDate and time: Tuesday, 17 January 2017, 9:30-11:30 Program1. Factor analyses of Japanese speech utilizing non-negative bases Power fluctuations of Japanese speech in 20 narrow frequency bands simulating the auditory periphery were subjected to a new type of factor analysis. Negative factor loadings were shifted to zero, and each variable was represented by the factor with the greatest factor loading. Thus, orthogonal non-negative bases were obtained. We resynthesized the speech by changing the intensity of each ‘factor’ utilizing the fluctuation of the corresponding factor score. It was shown that four factors were adequate to resynthesize reasonably intelligible speech. A big leap of intelligibility came out when the number of factors increased from 2 to 3, coinciding with our previous results. 2. Perceptual roles of 4 power-fluctuation factors in Japanese speech We performed a listening experiment to investigate perceptual roles of 4 power-fluctuation factors extracted from 20-critical-band power fluctuations of Japanese speech. The intelligibility of Japanese noise-vocoded speech outstandingly decreased when factor 2, which covered 500--1200 Hz, was eliminated. The results suggested that the information given by factor 2 was vital for speech intelligibility. 3. A peripheral model of gap detection Gap detection is an important measure of the temporal resolution of the auditory system. We present a model of gap detection involving the statistics of peripheral auditory neural activity: Detecting a gap involves the detection of an interval that is different from the usual interspike interval found in the auditory spike train. The model is capable of resolving a number of important observations in empirical gap research including why across-channel (or across-frequency) gap detection is an order of magnitude larger than gap detection performed in channel (i.e., using the same frequency). We achieve this by recognizing that in-channel detection involves a different strategy than across-channel detection. The model also provides an explanation for why the intensity dependence of gap detection is limited to a 40 dB range, and why critical bands are crucial towards defining the notion of a channel in gap detection. Specific predictions can be made about the shapes of the psychometric functions. |
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