A new model for binaural signal detection

Most present-day binaural models make use of coincidence detectors following an internal delay, so-called crosscorrelation models. We present a new modeling approach based on a subtractive mechanism as found in excitatory–inhibitory type neurons in the auditory pathway. This approach transforms, for each auditory filter, time-domain waveforms into a time-varying two-dimensional activity pattern, where each unit within that pattern has a characteristic interaural time delay and intensity difference. Limits of resolution are modeled by adding the same amount of internal noise to each unit. From this activity pattern, several features of the stimulus can be extracted, such as the apparent lateralization and the presence of a test signal within a masker. For modeling binaural detection it is assumed that a test signal must induce a significant change within the internal representation in order to be detectable. Depending on the condition, detection is limited by internal noise (NoS) or by external fluctuations (NS, 0.95). This model can be used as an artificial observer in the same way as described by Dau et al. [J. Acoust. Soc. Am. 99, 3615–3622 (1996)] for monaural signals