Experiments with the Hopkins Electronic EAR

We have developed hardware and software for continuous long-term recordings from the Hopkins Electronic EAR (HEEAR), an analog VLSI model of the auditory periphery designed in our laboratory [1]. Figure 1 shows the experimental setup. Previously recorded audio signals are used to stimulate the cochlear model. These signals can be downloaded to the rst PC's hard disk over an ethernet link. The PC converts the data le into analog values using a digital-to-analog converter module. The only limit to the length of the input le is the size of the rst PC's hard disk. The second PC can store up to 30 minutes of multi-channel analog signals from the model, sampling either 32 signals at 12 kHz or 16 signals at 24 kHz. The recorded data are sent back to a workstation for further analysis over a second ethernet link. All processing is performed by the HEEAR chip set in real-time, consuming less than 25 milliwatts of power, including external potentiometers used to set the parameters of the hardware model. We have designed the experimental setup with the goal of processing four half-hour segments from a standard database using the silicon cochlea. The outputs of the HEEAR chips will be used by another research group to train and test a large vocabulary speech recognition system. At the Speech Research Symposium, we will present preliminary results from a series of experiments which are being conducted using the Hopkins Electronic Ear. In our rst study, the silicon cochlea is stimulated using tone bursts with amplitudes which vary over one order of magnitude, in order to demonstrate the properties of adaptation and signal compression characteristic of auditory processors. The output of the cochlea is also studied in response to pure tones with and without additive white noise. In a third experiment, speech segments of one male and one female speaker are taken from a standard database. The clean speech is degraded with successively larger amounts of band-limited white noise, to obtain signal-to-noise ratios of 30 dB, 20 dB, 12 dB, 6 dB, and 0 dB. Using images similar to the neurogram [2], our intention is to give a qualitative demonstration of the HEEAR chips' ability to process speech robustly in the presence of noise.