Template-based personalized singing voice synthesis
Ling Cen, Minghui Dong, Paul Chan
Abstract
Ling Cen, Minghui Dong, Paul Chan
Abstract
In this paper, a template-based personalized singing voice synthesis method is proposed. It generates singing voices by means of conversion from the narrated lyrics of a song with the use of template recordings. The template voices are parallel speaking and singing voices recorded from professional singers, which are used to derive the transformation models for acoustic feature conversion. When converting a new instance of speech, its acoustic features are modified to approximate those of the actual singing voice based on the transformation models. Since the pitch contour of the synthesized singing is derived from an actual singing voice, it is more natural than modifying a step contour to implement pitch fluctuations such as overshoot and vibrato. It has been shown from the subjective tests that nearly natural singing quality with the preservation of the timbre can be achieved with the help of our method.
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In this paper, a template-based personalized singing voice synthesis method is proposed. It generates singing voices by means of conversion from the narrated lyrics of a song with the use of template recordings. The template voices are parallel speaking and singing voices recorded from professional singers, which are used to derive the transformation models for acoustic feature conversion. When converting a new instance of speech, its acoustic features are modified to approximate those of the actual singing voice based on the transformation models. Since the pitch contour of the synthesized singing is derived from an actual singing voice, it is more natural than modifying a step contour to implement pitch fluctuations such as overshoot and vibrato. It has been shown from the subjective tests that nearly natural singing quality with the preservation of the timbre can be achieved with the help of our method.
Key concepts: Singing, Vibrato, Timbre, Lyrics, Speech recognition, Computer science, Feature (linguistics), Natural (archaeology)