1. Jonas Braasch Architectural Acoustics Group Communication Acoustics and Aural Architecture Research Laboratory (C A 3 R L) Rensselaer Polytechnic Institute, Troy, NY http://symphony.arch.rpi.edu/~carl Simulating the precedence effect by means of autocorrelation

2. The precedence effect (Blauert Spatial Hearing, 1983) Localization Dominance region Summing localization region Region with two auditory events lead lag or interstimulus interval (ISI)

3. Objectives 1.Model should be able to focus on stationary (non-onset) cues 2.Analytical optimization of inhibition parameters 3.Accurate simulation of data with ILD cues

4. Time course Unusual approach using a monophonic lead/lag pair

5. Road Map 1.use autocorrelation to estimate lag parameters (lag delay and amplitude) 2.use a filter to eliminate lag from total signal 3.extent mechanism to comply with the concept of auditory bands 4.integrate algorithm in binaural model (e.g., eliminate lag in each channel) 5.evaluate model performance using literature data

6. t ≈a≈a Autocorrelation function (ACF) for a lead/lag pair (one channel) Stimulus: 100 ms/broadband noise burst (20-2000 Hz) Interstimulus Interval: 5 ms.

7. Lead/lag autocorrelation function

8. autocorrelation function decomposition

9. B A 00  relative lag amplitude

10. Filter Impulse Response ACF modelclassic inhibition approach   a|=a lag /a lead inhibition excitation  inh  a|=a inh Parameters not adapted to stimuli inhibition (no excitation) lag removal filter

11. lead only Lead+lag Lead, after lag removal error autocorrelation evaluation of filtered signal

12. auditory filter simulation

13. broadband AFC resynthesis Orthogonal for separate freqs

14. cross-correlation analysis for binaural signal

15. binaural model architecture

16. ISI=Interstimulus Interval lead position lag position model datapsychoacoustic data

17. exp of Colburn & Dizon (2006)

19. 1.Model processes sound based on stationary (non-onset) cues and accurate simulates of data with ILD cues 2.model optimizes inhibition parameters analytically Conclusions

20. Lindemann model Peak is off-center at position of the lead Simple Cross-correlation model Peak is on-center between the positions of lead and lag Lindemann Model (1985)

21. IIR filter to remove lag from lead/lag pair. influence of lag no lag ACF before filtering ACF after filtering