DocumentCode
178416
Title
Parametric representation for singing voice synthesis: A comparative evaluation
Author
Babacan, Onur ; Drugman, Thomas ; Raitio, Tuomo ; Erro, Daniel ; Dutoit, Thierry
Author_Institution
TCTS Lab., Univ. of Mons, Mons, Belgium
fYear
2014
fDate
4-9 May 2014
Firstpage
2564
Lastpage
2568
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.
Keywords
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; Frequency modulation; Harmonic analysis; Hidden Markov models; Speech; Speech synthesis; Stochastic processes; Vocoders; Parametric Representation; Singing Voice; Synthesis; Vocoder;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6854063
Filename
6854063
Link To Document