# CSSinger: End-to-End Chunkwise Streaming Singing Voice Synthesis System Based on Conditional Variational Autoencoder

arXiv: https://arxiv.org/abs/2412.08918 · HTML: https://mlsanity.com/paper/2412.08918/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Dec 2024.

## Built on by (most cited first, 2 of 2)

- [Conan: A Chunkwise Online Network for Zero-Shot Adaptive Voice Conversion](https://mlsanity.com/paper/2507.14534/) (2025)
- [Real-Time Interactive Music Generation via Data-Free Streaming Consistency Distillation](https://mlsanity.com/paper/2606.24307/) (2026)

## Abstract (arXiv)

Singing Voice Synthesis (SVS) aims to generate singing voices of high fidelity and expressiveness. Conventional SVS systems usually utilize an acoustic model to transform a music score into acoustic features, followed by a vocoder to reconstruct the singing voice. It was recently shown that end-to-end modeling is effective in the fields of SVS and Text to Speech (TTS). In this work, we thus present a fully end-to-end SVS method together with a chunkwise streaming inference to address the latency issue for practical usages. Note that this is the first attempt to fully implement end-to-end streaming audio synthesis using latent representations in VAE. We have made specific improvements to enhance the performance of streaming SVS using latent representations. Experimental results demonstrate that the proposed method achieves synthesized audio with high expressiveness and pitch accuracy in both streaming SVS and TTS tasks.