vocos
Fourier-based neural vocoder for high-quality audio synthesis
Decision gist · record as of 2026-08-14
Yes, if you need a fast neural vocoder for mel-spectrogram or EnCodec token-to-audio synthesis and can work with a dormant codebase. Low install friction and zero known vulnerabilities make it practical for inference. Verify the license status directly in the repository before commercial use, and be aware that maintenance has stalled since 2023-10-14—expect no active support or updates.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires torch and torchaudio; pre-trained models are downloaded from huggingface-hub on first use.
- Low install friction with a pure-Python wheel.
- Maintenance is dormant—last release was 2023-10-14 and last commit 2024-08-07—but the repository remains unarchived with moderate popularity (1150 stars).
License · maintenance · safety
(unclear) — License treatment is unclear; the repository states MIT in its LICENSE file, but the PyPI metadata does not declare it formally. Verify the LICENSE file directly before relying on the package in a commercial or license-sensitive context.
last release 2023-10-14 (1035 days) · last repo commit 2024-08-07 · 1,150 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 423,607 downloads/mo, #6,771 on PyPI
Alternatives
Verify before relying
pip install vocos
import torch
from vocos import Vocos
vocos = Vocos.from_pretrained("charactr/vocos-mel-24khz")
mel = torch.randn(1, 100, 256) # B, C, T
audio = vocos.decode(mel)- Whether the MIT license statement in the repository's LICENSE file is the authoritative license for the PyPI package.
- Whether the package is actively maintained or if dormancy signals a shift to a successor or fork.
- Compatibility with modern PyTorch and torchaudio versions beyond what the fact sheet specifies.
What it is and what it does
Vocos is a neural vocoder—a machine learning model that converts acoustic feature representations into audio waveforms. Unlike traditional vocoders that work in the time domain, Vocos generates spectral coefficients and reconstructs audio via inverse Fourier transform, enabling fast single-pass synthesis. It is trained using a GAN objective and can accept either mel-spectrograms or EnCodec tokens as input, making it suitable for integration into text-to-speech pipelines or audio processing workflows.
The package includes pre-trained models for 24 kHz audio synthesis and supports both inference and training modes. It depends on torch, torchaudio, numpy, scipy, einops, pyyaml, huggingface-hub, and encodec. Installation is straightforward, though the dormant maintenance status (last release 2023-10-14) means bug fixes and feature updates are not actively rolling out.
Use it for
- Convert mel-spectrograms from a text-to-speech model into high-quality audio waveforms for end-to-end TTS synthesis.
- Reconstruct audio from EnCodec-compressed tokens at various bandwidth levels for codec-based audio processing.
- Perform copy-synthesis by resampling an audio file to 24 kHz and reconstructing it through the vocoder.
- Integrate with text-to-audio models as a replacement vocoder for faster or higher-quality audio generation.
- Train a custom vocoder on domain-specific audio data using the provided training pipeline and configuration framework.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need a fast neural vocoder for mel-spectrogram or EnCodec token-to-audio synthesis and can work with a dormant codebase.
Low install friction and zero known vulnerabilities make it practical for inference. Verify the license status directly in the repository before commercial use, and be aware that maintenance has stalled since 2023-10-14—expect no active support or updates.
Install
vocos on PyPI
Before you install
Low install friction with a pure-Python wheel. Maintenance is dormant—last release was 2023-10-14 and last commit 2024-08-07—but the repository remains unarchived with moderate popularity (1150 stars).
Requires torch and torchaudio; pre-trained models are downloaded from huggingface-hub on first use.
License in practice
License treatment is unclear; the repository states MIT in its LICENSE file, but the PyPI metadata does not declare it formally. Verify the LICENSE file directly before relying on the package in a commercial or license-sensitive context.
Quickstart
pip install vocos
import torch
from vocos import Vocos
vocos = Vocos.from_pretrained("charactr/vocos-mel-24khz")
mel = torch.randn(1, 100, 256) # B, C, T
audio = vocos.decode(mel)Verify before relying
- Whether the MIT license statement in the repository's LICENSE file is the authoritative license for the PyPI package.
- Whether the package is actively maintained or if dormancy signals a shift to a successor or fork.
- Compatibility with modern PyTorch and torchaudio versions beyond what the fact sheet specifies.
Package facts
| License | Not declared unclear |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 8 packagestorchtorchaudionumpyscipyeinopspyyamlhuggingface-hubencodec |
| Maintenance | Dormant 1,035 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 423,607 / month, #6,771 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: vocos-0.1.0-py3-none-any.whl
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