Modeling Singing F0 With Neural Network Driven Transition-Sustain Models

Understand

This study focuses on generating fundamental frequency (F0) curves of singing voice from musical scores stored in a midi-like notation.

• Current statistical parametric approaches to singing F0 modeling meet difficulties in reproducing vibratos and the temporal details at note boundaries due to the oversmoothing tendency of statistical models.
• This paper presents a neural network based solution that models a pair of neighboring notes at a time (the transition model) and uses a separate network for generating vibratos (the sustain model).
• Predictions from the two models are combined by summation after proper enveloping to enforce continuity.