Area/Energy-Efficient Gammatone Filters Based on Stochastic Computation

Abstract

This paper introduces area/energy-efficient gammatone filters based on stochastic computation. The gammatone filter well expresses the performance of human auditory peripheral mechanism and has a potential of improving advanced speech communications systems, especially hearing assisting devices and noise robust speech-recognition systems. Using stochastic computation, a power-and-area hungry multiplier used in a digital filter is replaced by a simple logic gate, leading to area-efficient hardware. However, a straightforward implementation of the stochastic gammatone filter suffers from significantly low accuracy in computation, which results in a low dynamic range (a ratio of the maximum to minimum magnitude) due to a small value of a filter gain. To improve the computation accuracy, gain-balancing techniques are presented that represent the original gain as the product of multiple larger gains introduced at the second-order sections. In addition, dynamic scaling techniques are proposed that scales up small values only on stochastic domain in order to reduce the number of stochastic bits required while maintaining the computation accuracy. For performance comparisons, the proposed stochastic gammatone filters are designed and evaluated on taiwan semiconductor manufacturing company (TSMC) 65-nm CMOS technology. As a result, the proposed filter achieves an area reduction of 90.7% and an energy reduction of 91.8% in comparison with a fixed-point gammatone filter at the same sampling frequency and a comparable dynamic range.