Parametric Representation for Singing Voice Synthesis: a Comparative Evaluation

• URL: http://arxiv.org/abs/2006.04142v1
• Date: Sun, 7 Jun 2020 13:06:30 GMT
• Title: Parametric Representation for Singing Voice Synthesis: a Comparative Evaluation
• Authors: Onur Babacan, Thomas Drugman, Tuomo Raitio, Daniel Erro, Thierry Dutoit
• Abstract summary: The goal of this paper is twofold. First, a comparative subjective evaluation is performed across four existing techniques suitable for statistical parametric synthesis. The artifacts occurring in high-pitched voices are discussed and possible approaches to overcome them are suggested.
• Score: 10.37199090634032
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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