Text to speech (TTS), or speech synthesis, which aims to synthesize intelligible and natural
speech given text, is a hot research topic in speech, language, and machine learning …

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 …

In recent years, foundation models (FMs) such as large language models (LLMs) and latent
diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This …

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 …

The term “differentiable digital signal processing” describes a family of techniques in which
loss function gradients are backpropagated through digital signal processors, facilitating …

Scaling text-to-speech to a large and wild dataset has been proven to be highly effective in
achieving timbre and speech style generalization, particularly in zero-shot TTS. However …

We present the latest iteration of the voice conversion challenge (VCC) series, a bi-annual
scientific event aiming to compare and understand different voice conversion (VC) systems …

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 …

This paper introduces Opencpop, a publicly available high-quality Mandarin singing corpus
designed for singing voice synthesis (SVS). The corpus consists of 100 popular Mandarin …

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 …