Singing voice synthesis (SVS) systems are built to synthesize high-quality and expressive
singing voice, in which the acoustic model generates the acoustic features (eg, mel …

The lack of publicly available high-quality and accurately labeled datasets has long been a
major bottleneck for singing voice synthesis (SVS). To tackle this problem, we present …

High-fidelity multi-singer singing voice synthesis is challenging for neural vocoder due to the
singing voice data shortage, limited singer generalization, and large computational cost …

In pop music, accompaniments are usually played by multiple instruments (tracks) such as
drum, bass, string and guitar, and can make a song more expressive and contagious by …

In this paper, we propose VISinger, a complete end-to-end high-quality singing voice
synthesis (SVS) system that directly generates singing audio from lyrics and musical score …

High-fidelity singing voices usually require higher sampling rate (eg, 48kHz) to convey
expression and emotion. However, higher sampling rate causes the wider frequency band …

AI music composition is one of the most attractive and important topics in artificial
intelligence, music, and multimedia. The typical tasks in AI music composition include …

This paper presents Sinsy, a deep neural network (DNN)-based singing voice synthesis
(SVS) system. In recent years, DNNs have been utilized in statistical parametric SVS …

A vocoder is a conditional audio generation model that converts acoustic features such as
mel-spectrograms into waveforms. Taking inspiration from Differentiable Digital Signal …

AI-empowered music processing is a diverse field that encompasses dozens of tasks,
ranging from generation tasks (eg, timbre synthesis) to comprehension tasks (eg, music …