Spectral estimation properties of nonlinear auditory models for noisy signals

The simulation of an auditory model of the inner ear including the nonlinear transduction of the auditory nerves is discussed and a scheme of cortical processing is proposed. The output of the last stage of the model, called the ensemble interval histogram (EIH), is a cortical representation of speech in both time and frequency, similar to a spectrogram. A statistical analysis of the output of this system is performed for sinusoidal and noise inputs to determine the accuracy of spectral representation in terms of frequency, amplitude, resolution, etc. Some preliminary simulation results for sinusoid and noise input at two signal-to-noise ratios are shown. It is found that although the EIH may have noise robustness, its resolution is a decreasing function of frequency. In addition, the magnitude of the EIM is sensitive to the noise in the signal as well as other discretizations in the model. It appears that the area under the major peak in the histogram is a more consistent measure of the signal strength than the EIH amplitude