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Sigma-delta analog to LPC feature converters for portable recognition interfaces

By: Chakrabartty, S.; Gore, A.;

2009 / IEEE / 978-1-4244-3827-3

Description

This item was taken from the IEEE Conference ' Sigma-delta analog to LPC feature converters for portable recognition interfaces ' For many recognition systems, the feature extraction unit forms the most computationally intensive and power consuming component. In this paper, we present a design of an analog-to-information converter that directly produces a pulse-encoded representation of linear predictive coded (LPC) features corresponding to an input analog signal. At the core of proposed design is a sigma-delta modulation procedure that is embedded within a learning step. Measured results from a fabricated prototype in a 0.5�m CMOS technology demonstrate the real-time functionality of the learner in extracting 6-dimensional online LPC features from input speech signal while consuming only 450 �W.