Improved Auditory-Inspired Signal Processing Algorithm Design for Tracking Multiple Frequency Components

Abstract

An adaptive synchrony capture filterbank (SCFB) signal processing architecture for tracking signal frequency components was proposed in a previous paper. Detailed analysis and further improvements are presented here. The original SCFB signal processing architecture consisted of a fixed array of traditional, passive linear, gammatone filters in cascade with a bank of three adaptively tunable bandpass filters that form part of a frequency discriminator loop (FDL). The SCFB exhibits many desirable properties for processing speech, music, and other complex sounds. In this article, an improved SCFB architecture is presented along with detailed specification of parameters that yield better frequency tracking. This architecture combines a FDL with a phase-locked loop, a concept borrowed from communication systems, to acquire and track frequency components in a time-varying signal. This modified algorithm estimates frequencies with higher accuracy even in the presence of closely spaced tones in the input. The improved performance of the algorithm is demonstrated by comparing the mean square error in the frequency estimates of synthetic time-varying signals.