Speech deconvolution by recursive ARMA lattice filters

All-zero filters in tapped-delay-line or lattice implementations are commonly used for speech deconvolution. The analysis techniques are mostly non-recursive, operating on a block of data at a time. In this paper we present a recursive pole-zero lattice form for speech analysis. The algorithm is based on the recently developed square-root normalized lattice forms. A comparison between the performance of AR and ARMA lattice filters is presented, using synthetic data. Preliminary results using speech data are also discussed.