Comparison of ARMA modelling methods for low bit rate speech coding

There are two main parts of parametric speech coding algorithms such as codebook-excited linear prediction (CELP): the determination of the vocal tract filter parameters and the selection of the excitation signals based on a perceptual error criterion. The vocal tract includes the oral and nasal cavities depending on the type of speech segments (e.g. nasals and unvoiced fricatives). The contribution from the nasal tract suggests the need for an ARMA (or pole-zero) model instead of the conventional AR (pole only) model. The paper compares the performance of several ARMA modelling techniques in estimating the vocal tract filter parameters. The best method in terms of spectral fit and computational complexity is then applied to a CELP-type speech coding algorithm, with results which are superior to conventional AR models