Natural and expressive voices in multiple languages. For voice agents and brand ambassadors.
Follow the steps below to download and run the NVIDIA NIM inference microservice for this model on your infrastructure of choice.
$ docker login nvcr.io
Username: $oauthtoken
Password: <PASTE_API_KEY_HERE>
Refer Supported Models for full list of models.
export NGC_API_KEY=<PASTE_API_KEY_HERE>
docker run -it --rm --name=magpie-tts-multilingual \
--runtime=nvidia \
--gpus '"device=0"' \
--shm-size=8GB \
-e NGC_API_KEY=$NGC_API_KEY \
-e NIM_HTTP_API_PORT=9000 \
-e NIM_GRPC_API_PORT=50051 \
-p 9000:9000 \
-p 50051:50051 \
nvcr.io/nim/nvidia/magpie-tts-multilingual:latest
It may take a up to 30 minutes depending on your network speed, for the container to be ready and start accepting requests from the time the docker container is started.
Open a new terminal and run following command to check if the service is ready to handle inference requests
curl -X 'GET' 'http://localhost:9000/v1/health/ready'
If the service is ready, you get a response similar to the following.
{"ready":true}
Open a new terminal and run following commands to synthesize audio from text using sample client scripts.
Install the Nemotron Speech Python client package
sudo apt-get install python3-pip
pip install -U nvidia-riva-client
Download Nemotron Speech sample clients
git clone https://github.com/nvidia-riva/python-clients.git
Run Text to Speech inference in English (en-US)
python3 python-clients/scripts/tts/talk.py --server 0.0.0.0:50051 \
--language-code en-US \
--voice Magpie-Multilingual.EN-US.Aria \
--text "Hello, this is a speech synthesizer." \
--stream \
--output output_english.wav
Run Text to Speech inference in Spanish (es-US)
python3 python-clients/scripts/tts/talk.py --server 0.0.0.0:50051 \
--language-code es-US \
--voice Magpie-Multilingual.ES-US.Diego \
--text "Vamos al parque los domingos para jugar con nuestros amigos." \
--stream \
--output output_spanish.wav
Run Text to Speech inference in French (fr-FR)
python3 python-clients/scripts/tts/talk.py --server 0.0.0.0:50051 \
--language-code fr-FR \
--voice Magpie-Multilingual.FR-FR.Louise \
--text "Je vais au supermarché avec ma mère pour acheter des légumes." \
--stream \
--output output_french.wav
On running the above commands, the synthesized audio will be saved to files with corresponding names.
You can list available voices with following command.
python3 python-clients/scripts/tts/talk.py --server 0.0.0.0:50051 \
--list-voices
For more details on getting started with this NIM, visit the Nemotron Speech TTS NIM Docs.