Non-Negative Temporal Decomposition of Speech Parameters by Multiplicative Update Rules

摘要

I invented a non-negative temporal decomposition method for line spectral pairs and articulatory parameters based on the multiplicative update rules. These parameters are decomposed into a set of temporally overlapped unimodal event functions restricted to the range [0,1] and corresponding event vectors. When line spectral pairs are used, event vectors preserve their ordering property. With the proposed method, the RMS error of the measured and reconstructed articulatory parameters is 0.21 mm and the spectral distance of the measured and reconstructed line spectral pairs parameters is 2.0 dB. The RMS error and spectral distance in the proposed method are smaller than those in conventional methods. This technique will be useful for many applications of speech coding and speech modification.