Parametric Representation for Singing Voice Synthesis: a Comparative Evaluation
June 07, 2020 Β· Declared Dead Β· π IEEE International Conference on Acoustics, Speech, and Signal Processing
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Authors
Onur Babacan, Thomas Drugman, Tuomo Raitio, Daniel Erro, Thierry Dutoit
arXiv ID
2006.04142
Category
eess.AS: Audio & Speech
Cross-listed
cs.CL,
cs.SD
Citations
10
Venue
IEEE International Conference on Acoustics, Speech, and Signal Processing
Last Checked
3 months ago
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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