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F0 Modeling For Singing Voice Synthesizers with LSTM Recurrent Neural Networks
2015
Zenodo
In singing voice synthesis process, score and lyrics for a target song are converted to singing voice expression parameters such as F0, spectra and dynamics. However, this study aims to model and automatically generate F0 parameter by assuring expressiveness and human-likeness in final synthesized singing voice. Musical contexts are important factor on evolution of F0 through a singing performance. Thus, we propose a machine-learning framework that learns F0 of the singing from a set of real
doi:10.5281/zenodo.3755574
fatcat:44izjub7yjbivn7mrj6sf7h2ae