Enhanced Virtual Singers Generation by Incorporating Singing Dynamics to Personalized Text-to-speech-to-singing

Kantapon Kaewtip; Fernando Villavicencio; Fang-Yu Kuo; Mark Harvilla; Iris Ouyang; Pierre Lanchantin

ICASSP 2019accepted0 citations

Enhanced Virtual Singers Generation by Incorporating Singing Dynamics to Personalized Text-to-speech-to-singing

Kantapon Kaewtip, Fernando Villavicencio, Fang-Yu Kuo, Mark Harvilla, Iris Ouyang, Pierre Lanchantin

Abstract

We present in this work a strategy to enhance the quality of Text-to-Speech (TTS) based Singing Voice generation. Speech-to-singing refers to techniques transforming a spoken voice into singing, mainly by manipulating the duration and pitch of a spoken version of a song's lyrics. While this strategy efficiently preserves the speaker identity, the generated singing is not always perceived fully natural since the vocal conditions generally change between spoken and singing voice. By incorporating speaker-independent natural singing information to TTS-based Speech-to-Singing (STS) we positively impact the sound quality (e.g. reducing hoarseness), as it is shown in the subjective evaluation reported at the end of this paper.

BibTeX

@inproceedings{icassp2019_enhancedvirtuals,
  title = {Enhanced Virtual Singers Generation by Incorporating Singing Dynamics to Personalized Text-to-speech-to-singing},
  author = {Kantapon Kaewtip and Fernando Villavicencio and Fang-Yu Kuo and Mark Harvilla and Iris Ouyang and Pierre Lanchantin},
  booktitle = {ICASSP 2019},
  year = {2019}
}