Continuous-Time Analog Filters for Audio Edge Intelligence: Review and Analysis on Design Techniques

Silicon cochlea designs capture the functionality of the biological cochlea. Their use has been explored for cochlea prosthesis applications and more recently in edge audio devices which are required to support always-on operation. As their stringent power constraints pose several design challenges, IC designers are forced to look for solutions that use low standby power. One promising bio-inspired approach is to combine the continuous-time analog filter channels of the silicon cochlea with a small memory footprint deep neural network that is trained on edge tasks such as keyword spotting, thereby allowing all blocks to be embedded in an IC. This paper reviews the analog filter circuits used as feature extractors for current edge audio devices, starting with the original biquad filter circuits proposed for the silicon cochlea. Our analysis starts from the interpretation of a basic biquad filter as a two-integrator-loop topology and reviews the progression in the design of second-order low-pass and band-pass filters ranging from OTA-based to source-follower-based architectures. We also derive and analyze the small-signal transfer function and discuss performance aspects of these filters. The analysis of these different filter configurations can be applied to other application domains such as biomedical devices which employ a front-end bandpass filter.