High Fidelity Neural Audio Compression
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Neural Text-to-Speech Synthesis
Text-to-speech (TTS) aims to synthesize intelligible and natural speech based on the given text. It is a hot topic in language, speech, and machine learning research and has broad applications in industry. This book introduces neural network-based TTS in the era of deep learning, aiming to provide a good understanding of neural TTS, current research and applications, and the future research trend. This book first introduces the history of TTS technologies and overviews neural TTS, and provides preliminary knowledge on language and speech processing, neural networks and deep learning, and deep generative models. It then introduces neural TTS from the perspective of key components (text analyses, acoustic models, vocoders, and end-to-end models) and advanced topics (expressive and controllable, robust, model-efficient, and data-efficient TTS). It also points some future research directions and collects some resources related to TTS. This book is the first to introduce neural TTS in a comprehensive and easy-to-understand way and can serve both academic researchers and industry practitioners working on TTS.
Hands-On Generative AI with Transformers and Diffusion Models
Author: Omar Sanseviero
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2024-11-22
Learn to use generative AI techniques to create novel text, images, audio, and even music with this practical, hands-on book. Readers will understand how state-of-the-art generative models work, how to fine-tune and adapt them to their needs, and how to combine existing building blocks to create new models and creative applications in different domains. This go-to book introduces theoretical concepts followed by guided practical applications, with extensive code samples and easy-to-understand illustrations. You'll learn how to use open source libraries to utilize transformers and diffusion models, conduct code exploration, and study several existing projects to help guide your work. Build and customize models that can generate text and images Explore trade-offs between using a pretrained model and fine-tuning your own model Create and utilize models that can generate, edit, and modify images in any style Customize transformers and diffusion models for multiple creative purposes Train models that can reflect your own unique style
Building Generative AI Services with FastAPI
Author: Alireza Parandeh
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2025-04-15
Ready to build production-grade applications with generative AI? This practical guide takes you through designing and deploying AI services using the FastAPI web framework. Learn how to integrate models that process text, images, audio, and video while seamlessly interacting with databases, filesystems, websites, and APIs. Whether you're a web developer, data scientist, or DevOps engineer, this book equips you with the tools to build scalable, real-time AI applications. Author Alireza Parandeh provides clear explanations and hands-on examples covering authentication, concurrency, caching, and retrieval-augmented generation (RAG) with vector databases. You'll also explore best practices for testing AI outputs, optimizing performance, and securing microservices. With containerized deployment using Docker, you'll be ready to launch AI-powered applications confidently in the cloud. Build generative AI services that interact with databases, filesystems, websites, and APIs Manage concurrency in AI workloads and handle long-running tasks Stream AI-generated outputs in real time via WebSocket and server-sent events Secure services with authentication, content filtering, throttling, and rate limiting Optimize AI performance with caching, batch processing, and fine-tuning techniques Visit the Book's Website.