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arXiv · 2006.04142

Parametric Representation for Singing Voice Synthesis: a Comparative Evaluation

Onur Babacan·Thomas Drugman·Tuomo Raitio·Daniel Erro·Thierry Dutoit
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Abstract

Various parametric representations have been proposed to model the speech signal. While the performance of such vocoders is well-known in the context of speech processing, their extrapolation to singing voice synthesis might not be straightforward. The goal of this paper is twofold. First, a comparative subjective evaluation is performed across four existing techniques suitable for statistical parametric synthesis: traditional pulse vocoder, Deterministic plus Stochastic Model, Harmonic plus Noise Model and GlottHMM. The behavior of these techniques as a function of the singer type (baritone, counter-tenor and soprano) is studied. Secondly, the artifacts occurring in high-pitched voices are discussed and possible approaches to overcome them are suggested.

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Onur Babacan, Thomas Drugman, Tuomo Raitio, Daniel Erro, Thierry Dutoit. 2020-06-07. Parametric Representation for Singing Voice Synthesis: a Comparative Evaluation. https://arxiv.org/abs/2006.04142

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