Building Conversational AI Applications (BCAA) – Outline

Detailed Course Outline

Introduction

  • Meet the instructor.
  • Create an account at courses.nvidia.com/join

Introduction to Conversational AI

  • Explore the conversational AI landscape and gain a deeper understanding of the key components of ASR pipelines:
    • Work through an ASR model example from audio to spectrogram to text.
    • Explore decoders, customizations, and additional models, including inverse text normalization (ITN), punctuation and capitalization, and language identification.
    • Deploy Riva ASR.

Customized Conversational AI Pipelines

  • Explore the key components of the TTS pipeline and full pipeline customizations:
    • Explore the spectrogram generator model and the vocoder model.
    • Work with text normalization and grapheme to phoneme (G2P) conversion to customize pronunciations.
    • Deploy a full ASR-NLP-TTS custom pipeline in Riva.

Inference and Deployment Challenges

  • Explore challenges related to performance, optimization, and scaling in production deployment of conversational AI applications:
    • Gain an understanding of the inference deployment process.
    • Analyze non-functional requirements and their implications.
    • Use a Helm chart to deploy a conversational AI application with a Kubernetes cluster.

Final Review

  • Review key learnings and answer questions.
  • Complete the assessment and earn a certificate.
  • Complete the workshop survey.
  • Learn how to set up your own AI application development environment.