Parametric representation for singing voice synthesis: A comparative evaluation

Acoustics, Speech and Signal Processing(2014)

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摘要
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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关键词
hidden Markov models,speech synthesis,statistical analysis,vocoders,GlottHMM,baritone,counter-tenor,deterministic plus stochastic model,extrapolation,harmonic plus noise model,high-pitched voices,parametric representations,singer type,singing voice synthesis,soprano,speech processing,speech signal model,statistical parametric synthesis,traditional pulse vocoder,vocoders,Parametric Representation,Singing Voice,Synthesis,Vocoder
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