Sound source localization in real sound fields based on empirical statistics of interaural parameters

The role of temporal fluctuations and systematic variations of interaural parameters in localization of sound sources in spatially distributed, nonstationary noise conditions was investigated. For this, Bayesian estimation was applied to interaural parameters calculated with physiologically plausible time and frequency resolution. Probability density functions (PDFs) of the interaural level differences (ILDs) and phase differences (IPDs) were estimated by measuring histograms for a directional sound source perturbed by several types of interfering noise at signal-to-noise ratios (SNRs) between -5 and +30 dB. A moment analysis of the PDFs reveals that the expected values shift and the standard deviations increase considerably with decreasing SNR, and that the PDFs have non-Gaussian shape at medium SNRs. A d' analysis of the PDFs indicates that elevation discrimination is possible even at tow SNRs in the median plane by integrating information across frequency. Absolute sound localization was simulated by a Bayesian maximum a posteriori (MAP) procedure. The simulation is based on frequency integration of broadly tuned detectors. Confusion patterns of real and estimated sound source directions are similar to those of human listeners. The results indicate that robust processing strategies are needed to exploit interaural parameters successfully in noise conditions due to their strong temporal fluctuations. (c) 2006 Acoustical Society of America.