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How to Build your very own Google's NotebookLM
- The rising popularity of audio content consumption has led to the development of cloud services primarily aimed at converting documents to audio formats with natural language understanding and the ability to efficiently handle document formats while ensuring smooth user experiences.
- This article showcases how a similar system can be created using modern cloud services, including FastAPI, Firebase, Google Cloud Pub/Sub, and Azure's Text-to-Speech service, to generate high-quality podcasts.
- The system is designed to handle different formats, generate natural-sounding audio in multiple voices, process large-scale data, provide real-time status updates, maintain high scalability and availability, and deliver efficient data processing.
- FastAPI backend serves as the backend system and allows concurrent requests handling, runtime validation, and automatic interactive API documentation generation.
- Firebase provides two crucial services of Firebase Storage for automatic scaling and secure file uploads and Firestore for a real-time database for project status tracking.
- Google Cloud Pub/Sub is used as the messaging backbone that allows users to decouple the system's architecture across different messaging channels and messaging types and provides guarantees for message deliveries.
- The system applies Azure's Cognitive Services Speech SDK to generate natural-sounding voice synthesis, creating multi-voice podcasts using AI-supported speech recording, and supporting different host voices implemented through Azure voices.
- The worker component handles Document Analysis, Content Processing, and Audio Generation through batch processing, parallel processing, and resource-based autoscaling resource-based scaling with minimal additional operational overheads.
- A system for comprehensive error handling, status tracking, and resource cleanup is incorporated for reliable system operations.
- This document-to-podcast converter's current system provides a robust foundation for managing complex document processing at scale.
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