nvidia/fastpitch-hifigan-tts

RUN ANYWHERE

Expressive and engaging English voices for Q&A assistants, brand ambassadors, and service robots

nvidia nimtext-to-speech
API Reference

By running the below commands, you accept the NVIDIA AI Enterprise Terms of Use and the NVIDIA Community Models License.

Pull and run nvidia/fastpitch-hifigan-tts using Docker (this will download the full model and run it in your local environment)

$ 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>

export CONTAINER_NAME=fastpitch-hifigan-tts
docker run -it --rm --name=$CONTAINER_NAME \
  --runtime=nvidia \
  --gpus '"device=0"' \
  --shm-size=8GB \
  -e NGC_API_KEY=$NGC_API_KEY \
  -e NIM_HTTP_API_PORT=9000 \
  -e NIM_GRPC_API_PORT=50051 \
  -p 9000:9000 \
  -p 50051:50051 \
  -e NIM_TAGS_SELECTOR=name=fastpitch-hifigan-en-us \
  nvcr.io/nim/nvidia/riva-tts:1.3.0

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}

Install the Riva Python client package

sudo apt-get install python3-pip
pip install nvidia-riva-client

Download Riva sample clients

git clone https://github.com/nvidia-riva/python-clients.git

Run Text to Speech inference

python3 python-clients/scripts/tts/talk.py --server 0.0.0.0:50051 --text "Hello, this is a speech synthesizer." --language-code en-US --output output.wav

On running the above command, the synthesized audio file named output.wav will be created.

For more details on getting started with this NIM, visit the NVIDIA NIM Docs.