GraphCanon updated 3w · GitHub synced 3w
Decision brief
TensorFlowTTS is notable for its real-time speech synthesis capabilities with support for multiple languages and advanced models like Tacotron2, FastSpeech2, MelGAN.
Good fit when
- When you need state-of-the-art real-time text-to-speech functionality across several languages including English, French, Korean, Chinese, German,
- If your project requires the compatibility of TensorFlow 2.x for further integration or leveraging multi-GPU setups, especially with version 2.6 recommended by the developers for optimal performance
Avoid when
- When you require a text-to-speech solution that works on operating systems other than Ubuntu 18.04 as it has been tested only on this specific environment
- If your project cannot meet the hardware requirements such as needing CUDA 10.1 and CuDNN 7.6.5, or if you want to avoid dependency on TensorFlow-specific packages like TensorFlow Addons
Observed Jul 16, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (754d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install TensorFlowTTSSimilar 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
TensorFlowTTS is a real-time speech synthesis toolkit supporting multiple languages including English, French, Korean, Chinese, and German.
Capability facts
- Deploy
- Self-host
Source: dockerfile:docker-compose.yml · Jul 29, 2026
- Docker
- Dockerfile present
Source: dockerfile:docker-compose.yml · Jul 29, 2026
- Languages
- python
Source: github.language · Jul 29, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
Requirements
This repository is tested on Ubuntu 18.04 with:
- Python 3.7+
- Cuda 10.1
- CuDNN 7.6.5
- Tensorflow 2.2/2.3/2.4/2.5/2.6
- Tensorflow Addons >= 0.10.0
Different Tensorflow version should be working but not tested yet. This repo will try to work with the latest stable TensorFlow version. We recommend you install TensorFlow 2.6.0 to training in case you want to use MultiGPU.
License
All models here are licensed under the Apache 2.0
For agents
This page has a .md twin and JSON over the API.