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SPECIFICTION
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DiffSinger

github.com

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Spec score 7.8 #13 of 25 in AI Singing Voice Generators

What it is

DiffSinger is a free, open-source singing voice synthesis system built around a shallow diffusion mechanism. The maintained version adapts generated audio to 44.1 kHz and incorporates updated acoustic models plus faster diffusion sampling methods. Variance models and parameters provide control over pitch, energy, breathiness, and other vocal characteristics. The linked MakeDiffSinger project supplies dataset-building pipelines, including recording-slicing and labeling tools. Its guide describes preprocessing data, training models, and running inference on DS files with variance or acoustic models. Installation requires Python 3.10 or later, with PyTorch 2.4.0 or later recommended. ONNX is the deployment format. The repository links OpenUtau and DiffScope as production or deployment projects; DiffScope is an editor powered by DiffSinger and remains under development. Users prepare their own data and assets. The project prohibits generating another person’s voice without consent and includes a utility for removing speaker embeddings from checkpoints before distribution. Support channels include tutorials, GitHub issues and discussions, QQ, and Discord.

Spec sheet

Purpose
DiffSinger is a singing voice synthesis system based on a shallow diffusion mechanism.Read 4 Oct 2026 · github.com
Intended users
The project says its functionality is designed for production deployment and the singing voice synthesis community.Read 4 Oct 2026 · github.com
Deployment
The guide states that DiffSinger uses ONNX as its deployment format.Read 4 Oct 2026 · github.com
Support
The project points users to tutorials, GitHub issues and discussions, and QQ and Discord communication groups.Read 4 Oct 2026 · github.com
Audio quality
The maintained version adapts synthesized audio to a 44.1 kHz sampling rate instead of the original 24 kHz.Read 4 Oct 2026 · github.com
Control
Variance models and parameters allow prediction and control of pitch, energy, breathiness, and other aspects.Read 4 Oct 2026 · github.com
Dataset tools
The linked MakeDiffSinger project provides pipelines and tools for building DiffSinger datasets, including recording slicing and labeling tools.Read 4 Oct 2026 · github.com
Editor integration
The repository links OpenUtau and DiffScope as deployment or production projects; DiffScope is described as an editor powered by DiffSinger and is under development.Read 4 Oct 2026 · github.com
Installation
The getting-started guide requires Python 3.10 or later and recommends PyTorch 2.4.0 or later.Read 4 Oct 2026 · github.com
Model distribution
The getting-started guide includes a utility to remove speaker embeddings from a checkpoint for data security when distributing models.Read 4 Oct 2026 · github.com
Model improvements
The project integrates improved acoustic models and diffusion sampling acceleration algorithms.Read 4 Oct 2026 · github.com
Security and consent
The repository prohibits using its functionality to generate someone's voice without that person's consent.Read 4 Oct 2026 · github.com
Training and inference
The guide describes preprocessing datasets, training models, and running inference on DS files using variance or acoustic models.Read 4 Oct 2026 · github.com

Plans and prices

DiffSinger Free Apache-2.0 licensed repository · requires Python 3.10 or later · users prepare their own data and assets Read 4 Oct 2026 · github.com

Every DiffSinger plan and price →

Strong points and limits

Strong points

  • 44.1 kHz maintained audio output
  • Controllable pitch and vocal characteristics
  • Dataset preparation tools available
  • ONNX deployment format
  • Apache-2.0 repository

Limits

  • Requires self-hosting
  • Users supply data and assets
  • Python 3.10 or later required
  • DiffScope is under development

Who it suits

It is intended for singing voice synthesis developers and production users who can self-host, prepare data, and train or run models. ONNX deployment and linked editor projects support production workflows.

Verdict

DiffSinger offers a configurable, self-hosted workflow for creating singing voices, from dataset preparation through ONNX deployment. It requires technical setup and user-provided assets, with explicit consent and checkpoint-security guidance.

Where Specifiction places it

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