Quick Start Guide#

Important

The Riva SDK release only supports embedded (L4T) platforms. For x86 data center deployments, refer to Riva ASR NIM, Riva TTS NIM, and Riva NMT NIM documentation.

This is the starting point to try out Riva. Specifically, this Quick Start Guide enables you to deploy pretrained models on a local workstation and run a sample client.

Riva Speech AI Skills supports one architecture, Linux ARM64. This is referred to as embedded (ARM64) throughout this documentation.

For more information and questions, visit the NVIDIA Riva Developer Forum.

Note

Riva embedded (ARM64) is in public beta.

Prerequisites#

Before using Riva Speech AI, ensure you meet the following prerequisites:

  1. You have access and are logged into NVIDIA NGC. For step-by-step instructions, refer to the NGC Getting Started Guide.

  2. You have access to an NVIDIA Jetson Thor. For more information, refer to the Support Matrix.

  3. You have installed NVIDIA JetPack™ version 7.0 on the Jetson platform. For more information, refer to the Support Matrix.

  4. You have ~32 GB free disk space on Jetson as required by the default containers and models. If you are deploying any Riva model intermediate representation (RMIR) models, the additional disk space required is ~32 GB plus the size of the RMIR models.

  5. You have enabled the following power modes on the Jetson platform. These modes activate all CPU cores and clock the CPU/GPU at maximum frequency for achieving the best performance.

    sudo nvpmodel -m 0 (Jetson Thor, mode MAXN)

  6. You have set the default runtime to nvidia on the Jetson platform by adding the following line in the /etc/docker/daemon.json file. Restart the Docker service using sudo systemctl restart docker after editing the file.

    "default-runtime": "nvidia"

  7. Obtain a free trial license to install NVIDIA Riva. For more information, refer to the NVIDIA AI Enterprise Trial.

Deployment Guide#

There are one push-button deployment options to deploy Riva Speech AI, which use pretrained models available from the NGC catalog:

Local Docker: You can use the Quick Start scripts to set up a local workstation and deploy the Riva services using Docker. Continue with this guide to use the Quick Start scripts.

In addition to using pretrained models, Riva Speech AI can run with fine-tune custom models using NVIDIA NeMo. Refer to the Model Development with NeMo section for details regarding the advanced option to create a model repository with NVIDIA NeMo.

For detailed instructions on deploying and using specific Riva services, refer to the following quick start guides.