Résumé du cours
Learn to build and deploy a real time telemedicine application with transcription and named entity recognition capabilities.
Please note that once a booking has been confirmed, it is non-refundable. This means that after you have confirmed your seat for an event, it cannot be cancelled and no refund will be issued, regardless of attendance.
Moyens d'évaluation :
- Quiz pré-formation de vérification des connaissances (si applicable)
- Évaluations formatives pendant la formation, à travers les travaux pratiques réalisés sur les labs à l’issue de chaque module, QCM, mises en situation…
- Complétion par chaque participant d’un questionnaire et/ou questionnaire de positionnement en amont et à l’issue de la formation pour validation de l’acquisition des compétences
Objectifs
- 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.
Suite de parcours
Contenu
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.
Moyens Pédagogiques :