BCAANVNvidiaNV-BCAA2.0<ul> <li>How to customize and deploy ASR and TTS models on Riva.</li><li>How to build and deploy an end-to-end conversational AI pipeline, including ASR, NLP, and TTS models, on Riva.</li><li>How to deploy a production-level conversational AI application with a Helm chart for scaling in Kubernetes clusters.</li></ul><p><strong>Introduction</strong> </p> <ul> <li>Meet the instructor.</li><li>Create an account at courses.nvidia.com/join</li></ul><p><strong>Introduction to Conversational AI</strong> </p> <ul> <li>Explore the conversational AI landscape and gain a deeper understanding of the key components of ASR pipelines:<ul> <li>Work through an ASR model example from audio to spectrogram to text.</li><li>Explore decoders, customizations, and additional models, including inverse text normalization (ITN), punctuation and capitalization, and language identification.</li><li>Deploy Riva ASR.</li></ul></li></ul><p><strong>Customized Conversational AI Pipelines</strong> </p> <ul> <li>Explore the key components of the TTS pipeline and full pipeline customizations:<ul> <li>Explore the spectrogram generator model and the vocoder model.</li><li>Work with text normalization and grapheme to phoneme (G2P) conversion to customize pronunciations.</li><li>Deploy a full ASR-NLP-TTS custom pipeline in Riva.</li></ul></li></ul><p><strong>Inference and Deployment Challenges</strong> </p> <ul> <li>Explore challenges related to performance, optimization, and scaling in production deployment of conversational AI applications:<ul> <li>Gain an understanding of the inference deployment process.</li><li>Analyze non-functional requirements and their implications.</li><li>Use a Helm chart to deploy a conversational AI application with a Kubernetes cluster.</li></ul></li></ul><p><strong>Final Review </strong> </p> <ul> <li>Review key learnings and answer questions.</li><li>Complete the assessment and earn a certificate.</li><li>Complete the workshop survey.</li><li>Learn how to set up your own AI application development environment.</li></ul>- How to customize and deploy ASR and TTS models on Riva. - How to build and deploy an end-to-end conversational AI pipeline, including ASR, NLP, and TTS models, on Riva. - How to deploy a production-level conversational AI application with a Helm chart for scaling in Kubernetes clusters.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.1 jour500.00500.00500.00500.00500.00420.00500.00690.00