Stanley Kubrick's 1968 film 2001: A Space Odyssey famously featured HAL, a computer with the ability to hold lengthy conversations with his fellow space travelers. More than forty years later, we have advanced computer technology that Kubrick never imagined, but we do not have computers that talk and understand speech as HAL did. Is it a failure of our technology that we have not gotten much further than an automated voice that tells us to "say or press 1"? Or is there something fundamental in human language and speech that we do not yet understand deeply enough to be able to replicate in a computer? In The Voice in the Machine, Roberto Pieraccini examines six decades of work in science and technology to develop computers that can interact with humans using speech and the industry that has arisen around the quest for these technologies. He shows that although the computers today that understand speech may not have HAL's capacity for conversation, they have capabilities that make them usable in many applications today and are on a fast track of improvement and innovation. Pieraccini describes the evolution of speech recognition and speech understanding processes from waveform methods to artificial intelligence approaches to statistical learning and modeling of human speech based on a rigorous mathematical model -- specifically, Hidden Markov Models (HMM). He details the development of dialog systems, the ability to produce speech, and the process of bringing talking machines to the market. Finally, he asks a question that only the future can answer: will we end up with HAL-like computers or something completely unexpected?
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Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
The math content is kept to a minimum to focus on what matters-applying the concepts in useful contexts. This book is sure to benefit anyone curious about the fascinating field of machine learning.
By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects.
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