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Lossy Speech Compression Via Compressed Sensing-Based Kalman Filtering

We present a new algorithm for lossy speech compression. The new algorithm is based on a simple technique for embedding a compressed sensing mechanism within a conventional Kalman filter. As such, it is capable of constructing compressed representations using significantly less samples than what is usually considered necessary.

By: Avishy Carmi; Dimitri Kanevsky; Bhuvana Ramabhadran

Published in: RC24814 in 2009

rc24814.pdf

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