Congratulations! You have completed the Audio Transcription AI workflow lab. This NVIDIA AI solution workflow is a reference to enable you to build your own AI solution with minimal preparation. It includes enterprise-ready implementation best practices ranging from authentication, monitoring, reporting, and load balancing, helping you achieve the desired AI outcome more quickly while allowing a path for you to deviate.
To further you along, an AI readiness assessment can help you understand and achieve your business need outcome.
What is your speech use case?
Are you using transcription and/or virtual assistants today?
Which languages are must-haves for your use case?
Where do you want to deploy speech applications? On-premises, in the cloud, at the edge?
What is your deployment timeline? When do you expect to see value?
How do you plan to deploy speech AI pipelines in production?
Are you planning to build your own internally?
Purchase from a software vendor?
Work with a system integrator?
Learn more about how Deutsche Bank and NVIDIA are accelerating the adoption of AI for Financial Services.
Read about Speech AI Solutions Enabled by NVIDIA
Reinvent Contact Center Experiences with NVIDIA Riva Transcription
Speech AI Web Page
Learn More about NVIDIA Speech AI Technologies
Essential Guide to Automatic Speech Recognition Technology Blog
Riva Solution Brief
Evaluate NVIDIA Speech AI Solutions
Riva on LaunchPad
Creating Voice-Based Virtual Assistants Using NVIDIA Riva & Rasa
Building Transcription & Entity Recognition Apps Using NVIDIA Riva
Building a Speech-Enabled AI Virtual Assistant with NVIDIA Riva on Amazon EC2
Developing the Next Generation of Extended Reality Applications with Speech AI
Reducing Development Time for Intelligent Virtual Assistants in Contact Centers
As you invest in AI, NVIDIA and our partners are your trusted advisors in helping you deploy AI solutions across various use cases. NVIDIA Data Science Professional Services are available to help ensure success by providing personalized guidance for speech AI use cases, including data preparation, model selection, domain customization, and performance improvement.