Parametric emotional singing voice synthesis

This paper describes an algorithm to control the expressed emotion of a synthesized song. Based on the database of various melodies sung neutrally with restricted set of words, hidden semi-Markov models (HSMMs) of notes ranging from E3 to G5 are constructed for synthesizing singing voice. Three steps are taken in the synthesis: (1) Pitch and duration are determined according to the notes indicated by the musical score; (2) Features are sampled from appropriate HSMMs with the duration set to the maximum probability; (3) Singing voice is synthesized by the mel-log spectrum approximation (MLSA) filter using the sampled features as parameters of the filter. Emotion of a synthesized song is controlled by varying the duration and the vibrato parameters according to the Thayer´s mood model. Perception test is performed to evaluate the synthesized song. The results show that the algorithm can control the expressed emotion of a singing voice given a neutral singing voice database.