magpie-tts-multilingual Model by NVIDIA

Getting Started

Riva uses gRPC APIs. Instructions below demonstrate usage of magpie-tts-multilingual model using Python gRPC client.

Prerequisites

You will need a system with Git and Python 3+ installed.

Install Riva Python Client

pip install -U nvidia-riva-client

Download Python Client

Download Python client code by cloning Python Client Repository.

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

Run Python Client

Open a command terminal and execute below command to synthesize audio from the example text. If you have generated the API key, it will be auto-populated in the command.

python python-clients/scripts/tts/talk.py \
    --server grpc.nvcf.nvidia.com:443 --use-ssl \
    --metadata function-id "877104f7-e885-42b9-8de8-f6e4c6303969"  \
    --metadata authorization "Bearer $NVIDIA_API_KEY" \
    --language-code en-US \
    --text "this audio is generated from nvidia's text to speech model" \
    --voice "Magpie-Multilingual.EN-US.Aria" \
    --output audio.wav

List of available voices can be obtained using below command.

python python-clients/scripts/tts/talk.py \
    --server grpc.nvcf.nvidia.com:443 --use-ssl \
    --metadata function-id "877104f7-e885-42b9-8de8-f6e4c6303969"  \
    --metadata authorization "Bearer $NVIDIA_API_KEY" \
    --list-voices

Support for gRPC clients in other languages

Riva uses gRPC APIs. Proto files can be downloaded from Riva gRPC Proto files and compiled to target language using Protoc compiler. Example Riva clients in C++ and Python languages are provided below.