NVIDIA Riva
NVIDIA® Riva, a premium edition of NVIDIA AI Enterprise software, is a GPU-accelerated speech and translation AI software development kit for building and deploying fully customizable, real-time AI pipelines that deliver world-class accuracy in all clouds, on premises, at the edge, and on embedded devices.
See Riva in Action
Try NVIDIA Riva Automatic Speech Recognition
Select the language and check out how Riva ASR delivers highly accurate transcription in real time by providing an input through your microphone or uploading a .wav file from your device.
Note: The duration of each sample is limited to 30 seconds.
Try NVIDIA Riva Text-to-Speech
Select a voice and type in a test sentence to hear Riva’s out-of-the-box English female or male voice.
Note: Input text is limited to 400 characters.
Use of Riva skills is subject to NVIDIA Riva terms of use. Your data will be used to improve NVIDIA products and services.
Ways to Get Started With NVIDIA Riva
Purchase Riva for Production Deployment
Get unlimited usage on all clouds, access to NVIDIA AI experts, and long-term support for production deployments with a purchase of NVIDIA Riva.
Contact Us to Learn More About Purchasing Riva Apply to Try Riva on NVIDIA LaunchPad
Get Access to Riva AI Workflows
Accelerate development time with packaged AI workflows for audio transcription and intelligent virtual assistants.
Learn More About the Transcription Workflow Learn More About the Intelligent Virtual Assistant Workflow
Download Containers and Models for Development
Develop multilingual voice-enabled applications for cloud, data center, or embedded deployments with Riva containers and pretrained models, available in a free 90-day trial on NVIDIA NGC™ to members of the NVIDIA Developer Program.
Download Now for Cloud and Data Center Download Now for Embedded
Introductory Resources
Quick-Start Guide
Get step-by-step instructions for deploying pretrained models as services on a local workstation and how to interact with them through a client.
Introductory Blog
Learn about Riva’s architecture, key features, and components for building speech and translation AI services.
Introductory Webinar
Build and deploy end-to-end speech and translation AI pipelines using NVIDIA Riva.
Use-Case Demo
See how Computacenter, Tarteel, Floatbot, Minerva CQ and others use Riva for multilingual transcription, translation, and voice of their agent assists, AI virtual assistants, and digital humans.
Development Starter Kits
Access everything you need to start developing your speech and translation AI application with NVIDIA Riva containers and models, including tutorials, notebooks, forums, release notes, and documentation.
Automatic Speech Recognition
Achieve high transcription accuracy for Arabic, English, French, German, Hindi, Italian, Japanese, Korean, Mandarin, Portuguese, Russian, and Spanish with state-of-the-art models pretrained on thousands of hours of audio on NVIDIA supercomputers.
Text-to-Speech
Customize across English, French, German, and Italian TTS pipelines for the voice and intonation you want.
Neural Machine Translation
Integrate highly accurate text-to-text, speech-to-text, or speech-to-speech translation for up to 31 languages into your conversational application pipelines.
Demo Video Tutorials
Learn to set up and start using Riva—from accessing NVIDIA NGC and working with the Riva Skills Quick Start guide, to running inference with ASR, TTS, and NMT models.
The Basics of NVIDIA NGC
Watch Video
Quick Start Guide for Riva
Watch Video
Exploring Riva’s Capabilities
Watch VideoSelf-Paced Training
Learn anytime, anywhere, with just a computer and an internet connection through the NVIDIA Deep Learning Institute (DLI).
Riva Speech API Demo
Take This DLI Course
Get Started With Highly Accurate Custom ASR for Speech AI
Take This DLI CourseNVIDIA platforms and application frameworks enable developers to build a wide array of AI applications. Consider potential algorithmic bias when choosing or creating the models being deployed. Also, work with the model’s developer to ensure that it meets the requirements for the relevant industry and use case; that the necessary instruction and documentation are provided to understand error rates, confidence intervals, and results; and that the model is being used under the conditions and in the manner intended.