ARMA speech analysis as a means for studying articulation
Louis Boves, Johan de Veth · The Journal of the Acoustical Society of America · 1987
It is well documented that linear prediction analysis will only allow prediction coefficients to relate to vocal tract shapes under very special conditions, and that the problems in interpreting LP analysis results in articulatory terms are due to the simplifying assumptions underlying the analysis model. Usually, the assumption that the system is all pole [or auto-regressive (AR)] is thought to be the most important simplification. Therefore, it is hoped that the use of the less restrictive pole-zero [or auto-regressive moving average (ARMA)] analysis model will offer greater opportunities for an articulatory interpretation. A detailed study of a number of different ARMA analysis implementations has shown that the all-pole assumption may not be the most important restriction on the articulatory interpretation of the analysis results; the assumption of Gaussian excitation may prove to be at least equally impeding. [Research supported by the Foundation for Speech Technology, funded by SPIN.]