Title :
Spectral estimation properties of nonlinear auditory models for noisy signals
Author :
Sreeniva, T.V. ; Singh, Karamjeet ; Niederjohn, R.J. ; Heinen, J.A.
Author_Institution :
Dept. of Electr., Comput., & Biomed. Eng., Marquette Univ., Milwaukee, WI, USA
Abstract :
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
Keywords :
hearing; physiological models; auditory nerves; cortical processing scheme; ensemble interval histogram; inner ear; model discretization; noisy signals; nonlinear auditory models; nonlinear transduction; signal strength; spectral estimation properties; spectrogram; speech representation; statistical analysis; Ear; Frequency; Histograms; Noise level; Noise robustness; Signal resolution; Signal to noise ratio; Spectrogram; Speech; Statistical analysis;
Conference_Titel :
Engineering in Medicine and Biology Society, 1989. Images of the Twenty-First Century., Proceedings of the Annual International Conference of the IEEE Engineering in
Conference_Location :
Seattle, WA
DOI :
10.1109/IEMBS.1989.95928
