Operation Whisper

Meet Morris and Lona Cohen, an ordinary-seeming couple living on a teacher's salary in a nondescript building on the East Side of New York City. On a hot afternoon in the autumn of 1950, a trusted colleague knocked at their door, held up a finger for silence, then began scribbling a note: Go now. Leave the lights on, walk out, don't look back. Born and raised in the Bronx and recruited to play football at Mississippi State, Morris Cohen fought for the Loyalists in the Spanish Civil War and with the U.S. Army in World War II. He and his wife, Lona, were as American as football and fried chicken, but for one detail: they'd spent their entire adult lives stealing American military secrets for the Soviet Union. And not just any military secrets, but a complete working plan of the first atomic bomb, smuggled direct from Los Alamos to their Soviet handler in New York. Their associates Julius and Ethel Rosenberg, who accomplished far less, had just been arrested, and the prosecutor wanted the death penalty. Did the Cohens wish to face the same fate? Federal agents were in the neighborhood, knocking on doors, getting close. So get out. Take nothing. Tell no one. In Operation Whisper, Barnes Carr tells the full, true story of the most effective Soviet spy couple in America, a pair who vanished under the FBI's nose only to turn up posing as rare book dealers in London, where they continued their atomic spying. The Cohens were talented, dedicated, worldly spies - an urbane, jet-set couple loyal to their service and their friends, and very good at their work. Most people they met seemed to think they represented the best of America. The Soviets certainly thought so.

Master automatic speech recognition (ASR) with groundbreaking generative AI for unrivaled accuracy and versatility in audio processing Key Features Uncover the intricate architecture and mechanics behind Whisper's robust speech recognition Apply Whisper's technology in innovative projects, from audio transcription to voice synthesis Navigate the practical use of Whisper in real-world scenarios for achieving dynamic tech solutions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs the field of generative AI evolves, so does the demand for intelligent systems that can understand human speech. Navigating the complexities of automatic speech recognition (ASR) technology is a significant challenge for many professionals. This book offers a comprehensive solution that guides you through OpenAI's advanced ASR system. You’ll begin your journey with Whisper's foundational concepts, gradually progressing to its sophisticated functionalities. Next, you’ll explore the transformer model, understand its multilingual capabilities, and grasp training techniques using weak supervision. The book helps you customize Whisper for different contexts and optimize its performance for specific needs. You’ll also focus on the vast potential of Whisper in real-world scenarios, including its transcription services, voice-based search, and the ability to enhance customer engagement. Advanced chapters delve into voice synthesis and diarization while addressing ethical considerations. By the end of this book, you'll have an understanding of ASR technology and have the skills to implement Whisper. Moreover, Python coding examples will equip you to apply ASR technologies in your projects as well as prepare you to tackle challenges and seize opportunities in the rapidly evolving world of voice recognition and processing.What you will learn Integrate Whisper into voice assistants and chatbots Use Whisper for efficient, accurate transcription services Understand Whisper's transformer model structure and nuances Fine-tune Whisper for specific language requirements globally Implement Whisper in real-time translation scenarios Explore voice synthesis capabilities using Whisper's robust tech Execute voice diarization with Whisper and NVIDIA's NeMo Navigate ethical considerations in advanced voice technology Who this book is for Learn OpenAI Whisper is designed for a diverse audience, including AI engineers, tech professionals, and students. It's ideal for those with a basic understanding of machine learning and Python programming, and an interest in voice technology, from developers integrating ASR in applications to researchers exploring the cutting-edge possibilities in artificial intelligence.