In this paper, a cost-effective implementation of a programmable filterbank front-end for speech recognition is presented. The objective has been to design a real-time bandpass filtering system with a filterbank of 16 filters, with analog audio input and analog output. The output consists of 16 analog signals, which are the envelopes of the filter outputs of the audio signal. These analog signals are then led to an analog neural computer, which performs the feature-based recognition task. One of the main objectives has been to allow the user to easily change the filter specifications without affecting the remaining system, thus a software implementation of the filterbank was preferred. In addition, the neural computer requires analog input. Therefore, we implemented the filterbank on a PC, with the input A/D and the output D/A performed by the PC stereo soundcard. Since multiple analog outputs are necessary for the neural computer (one for each filter), it then follows that the soundcard output should contain the multiplexed 16 filter outputs, while a hardware module is needed for demultiplexing the soundcard output into the final 16 analog signals.
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