Investigating source and filter contributions, and their interaction, to statistical parametric speech synthesis
Thomas Wayne Merritt, Tuomo Raitio, Simon King · 2014
This paper presents an investigation of the separate perceptual degradations introduced by the modelling of source and fil-ter features in statistical parametric speech synthesis. This is achieved using stimuli in which various permutations of natu-ral, vocoded and modelled source and filter are combined, op-tionally with the addition of filter modifications (e.g. global variance or modulation spectrum scaling). We also examine the assumption of independence between source and filter pa-rameters. Two complementary perceptual testing paradigms are adopted. In the first, we ask listeners to perform “same or differ-ent quality ” judgements between pairs of stimuli from different configurations. In the second, we ask listeners to give an opin-ion score for individual stimuli. Combining the findings from these tests, we draw some conclusions regarding the relative contributions of source and filter to the currently rather limited naturalness of statistical parametric synthetic speech, and test whether current independence assumptions are justified. Index Terms: speech synthesis, hidden Markov modelling, GlottHMM, source filter model, source filter interaction