Awesome
NOTE: Please see coqui-docker for docker images of Coqui TTS (Mozilla TTS's successor)
Mozilla TTS
Multi-platform Docker images for Mozilla TTS. Many thanks to erogol and the community!
Supported languages (see Released Models):
- U.S. English (
en
) - Spanish (
es
) - French (
fr
) - German (
de
)- Tacotron2 DDC model trained from Thorsten dataset
- Parallel WaveGAN model trained from same dataset
- Note: due to a mistake at training configuration, this model does not read numbers written in digit form.
Supported platforms:
x86_64
- GPU is not supported (no CUDA or GPU-enabled PyTorch)
- Your CPU must support AVX instructions (no Celeron, etc.)
armv7
- Raspberry Pi 2/3/4 (32-bit)
arm64
- Raspberry Pi 2/3/4 (64-bit)
RAM Limitations
If you're running on a Raspberry Pi with only 1 GB of RAM, you may be unable to load some of the larger models without increasing your swap space. To do this, simply edit the /etc/dphys-swapfile
file (with sudo
) and increase CONF_SWAPSIZE
(1000 is recommended, value is MB). Make sure to reboot after editing this file.
Using
$ docker run -it -p 5002:5002 synesthesiam/mozillatts:<LANGUAGE>
where <LANGUAGE>
is one of the supported languages (en
, es
, fr
, de
). If no language is given, U.S. English is used.
Visit http://localhost:5002 for web interface.
Do an HTTP GET at http://localhost:5002/api/tts?text=your%20sentence to get WAV audio back:
$ curl -G --output - \
--data-urlencode 'text=Welcome to the world of speech synthesis!' \
'http://localhost:5002/api/tts' | \
aplay
HTTP POST is also supported:
$ curl -X POST -H 'Content-Type: text/plain' --output - \
--data 'Welcome to the world of speech synthesis!' \
'http://localhost:5002/api/tts' | \
aplay
A /process
endpoint is available for compatibility with MaryTTS. Expose the correct port (59125) for maximum compatibility:
$ docker run -it -p 59125:5002 synesthesiam/mozillatts
You should now be able to use software like the Home Assistant MaryTTS integration.
Note that only the INPUT_TEXT
field is actually used.
Custom Model
The Docker image is usually built with buildx for multi-platform support. If you just want to build an image for one platform, you can do this:
$ NOBUILDX=1 LANGUAGE=en scripts/build-docker.sh
When you set a LANGUAGE
, the build script looks in model/<LANGUAGE>
. These files should exist:
model/<LANGUAGE>/config.json
model/<LANGUAGE>/checkpoint.pth.tar
(any name that ends in.pth.tar
is fine)model/<LANGUAGE>/scale_stats.npy
(optional)
Optionally, you may also include a vocoder:
model/<LANGUAGE>/vocoder/config.json
model/<LANGUAGE>/vocoder/checkpoint.pth.tar
(any name that ends in.pth.tar
is fine)model/<LANGUAGE>/vocoder/scale_stats.npy
(optional)
If the sample rates between the model and vocoder don't match, the audio will be interpolated.
Docker Download Cache
When building the Docker image, the download
directory may contain architecture-specific Python wheels. The download/amd64
directory, for example, will be used with pip's --find-links
on x86_64
systems.
The download/shared
directory is used for all architectures. If a requirements.txt
file is present there, it is used to install dependencies for MozillaTTS. This can be used to exclude Tensorflow, etc., or to use specific package versions.
Use Docker buildx
To use buildx
, you'll need to enable experimental features in the Docker CLI and then set up a private registry:
$ docker run -d -p 15555:5000 --name registry --restart=always registry:2
This registry runs on port 15555. Next, create a configuration file at /etc/docker/buildx.conf
with this inside:
[registry."localhost:15555"]
http = true
insecure = true
Note the same port number (15555). Finally, run the following commands to create a builder:
$ docker run --rm --privileged multiarch/qemu-user-static --reset -p yes
$ docker buildx create --config /etc/docker/buildx.conf --use --name mybuilder
$ docker buildx use mybuilder
$ docker buildx inspect --bootstrap
For some reason, these have to be run again after every reboot and will sometimes require removing the builder first.
If all is well, you can build for specific platforms like this:
$ PLATFORMS=linux/arm/v7 LANGUAGE=en DOCKER_REGISTRY=localhost:15555 scripts/build-docker.sh
Note that the limiting factor for most platforms is a compiled PyTorch wheel. Pre-built wheels are available here for ARM and PyTorch 1.6.0. Put wheels in the download
directory before building.