Now the generally used approaches such as auto-correlation method and covariance method for estimating LPC coefficients are to solve a set of linear equations by using of Levinson-Durbin recursion or lattice formulations, but the LPC coefficients computed are best only in the sense of L2 criterion. For speech processing, L&inf; criterion is a more suitable measure metric. The idea of our approach is: from the initial values of LPC coefficients, the residual errors could be reduced step by step by using Least Squares process iteratively until the LPC coefficients are approximately best in the sense of L&inf; criterion. Furthermore, this approach could be applied to other problems for estimating some parameters.
Cite as: Sen, Z., Shirai, K. (2000) Re-estimation of LPC coefficients in the sense of l&inf; criterion. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 1, 737-740, doi: 10.21437/ICSLP.2000-183
@inproceedings{sen00_icslp,
author={Zhang Sen and Katsuhiko Shirai},
title={{Re-estimation of LPC coefficients in the sense of l&inf; criterion}},
year=2000,
booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
pages={vol. 1, 737-740},
doi={10.21437/ICSLP.2000-183}
}