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Decision brief
🐸TTS is a Python-based deep learning toolkit for developing text-to-speech systems featuring models like Tacotron and Vocoder for training.
Good fit when
- If you are working on research projects that require advanced models such as Glow-TTS, HifiGAN, or MelGAN for high-quality speech synthesis
- When you need a tool that supports multiple speaker configurations and can train multi-speaker TTS models effectively
Avoid when
- If your project strictly requires a lightweight installation without the overhead of extra dependencies included when installing 🐸TTS from source for development purposes
- In cases where you are restricted to older Python versions less than 3.9, as 🐸TTS is tested on systems with python >= 3.9 but < 3.12
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (711d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- 137 low (137 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install TTSSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A Python-based deep learning toolkit for creating text-to-speech systems, featuring models like Tacotron and Vocoder, and training capabilities.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Jul 29, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Jul 29, 2026
- Languages
- python
Source: github.language+pyproject.toml · Jul 29, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 29, 2026)
🐸TTS is tested on Ubuntu 18.04 with **python >= 3.9, < 3.12.**.Source link
Tags
README
Installation
🐸TTS is tested on Ubuntu 18.04 with python >= 3.9, < 3.12..
If you are only interested in synthesizing speech with the released 🐸TTS models, installing from PyPI is the easiest option.
pip install TTS
If you plan to code or train models, clone 🐸TTS and install it locally.
git clone https://github.com/coqui-ai/TTS
pip install -e .[all,dev,notebooks] # Select the relevant extras
If you are on Ubuntu (Debian), you can also run following commands for installation.
$ make system-deps # intended to be used on Ubuntu (Debian). Let us know if you have a different OS.
$ make install
If you are on Windows, 👑@GuyPaddock wrote installation instructions here.
Docker Image
You can also try TTS without install with the docker image. Simply run the following command and you will be able to run TTS without installing it.
docker run --rm -it -p 5002:5002 --entrypoint /bin/bash ghcr.io/coqui-ai/tts-cpu
python3 TTS/server/server.py --list_models #To get the list of available models
python3 TTS/server/server.py --model_name tts_models/en/vctk/vits # To start a server
You can then enjoy the TTS server here More details about the docker images (like GPU support) can be found here
For agents
This page has a .md twin and JSON over the API.