The Voice in the Machine

The Voice in the Machine

Author: Roberto Pieraccini

Publisher: MIT Press

Published: 2012

Total Pages: 355

ISBN-13: 0262016850

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An examination of more than sixty years of successes and failures in developing technologies that allow computers to understand human spoken language. 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?


Machine Learning for Kids

Machine Learning for Kids

Author: Dale Lane

Publisher: No Starch Press

Published: 2021-01-19

Total Pages: 290

ISBN-13: 1718500572

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A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+


Signals, Instrumentation, Control, And Machine Learning: An Integrative Introduction

Signals, Instrumentation, Control, And Machine Learning: An Integrative Introduction

Author: Joseph Bentsman

Publisher: World Scientific

Published: 2022-03-07

Total Pages: 844

ISBN-13: 9811251886

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This book stems from a unique and a highly effective approach to introducing signal processing, instrumentation, diagnostics, filtering, control, system integration, and machine learning.It presents the interactive industrial grade software testbed of mold oscillator that captures the distortion induced by beam resonance and uses this testbed as a virtual lab to generate input-output data records that permit unravelling complex system behavior, enhancing signal processing, modeling, and simulation background, and testing controller designs.All topics are presented in a visually rich and mathematically well supported, but not analytically overburdened format. By incorporating software testbed into homework and project assignments, the narrative guides a reader in an easily followed step-by-step fashion towards finding the mold oscillator disturbance removal solution currently used in the actual steel production, while covering the key signal processing, control, system integration, and machine learning concepts.The presentation is extensively class-tested and refined though the six-year usage of the book material in a required engineering course at the University of Illinois at Urbana-Champaign.


Introduction to Ergonomics, Second Edition

Introduction to Ergonomics, Second Edition

Author: Robert Bridger

Publisher: CRC Press

Published: 2008-06-26

Total Pages: 563

ISBN-13: 0203504917

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When faced with productivity problems in the workplace, engineers might call for better machines, and management might call for better-trained people, but ergonomists call for a better interface and better interaction between the user and the machine. Introduction to Ergonomics, 2nd Edition, provides a comprehensive introduction to ergonomics as the study of the relationship between people and their working environment. The author presents evidence from field trials, studies and experiments that demonstrate the value of ergonomics in making the workplace safer, more error resistant, and compatible with users' characteristics and psychological and social needs. Evidence for the effectiveness of each topic is incorporated throughout the book as well, which helps practitioners to make the case for company investment in ergonomics. In addition, the author outlines international standards for ergonomics that influence engineering and design and pave the way for a more precise form of practice. Extensively revised and updated, this second edition explains the main areas of application, the science that underpins these applications, and demonstrates the cost-effectiveness of implementing the applications in a wide variety of work settings.


LSAT Logical Reasoning Prep: Complete Strategies and Tactics for Success on the LSAT Logical Reasoning Sections

LSAT Logical Reasoning Prep: Complete Strategies and Tactics for Success on the LSAT Logical Reasoning Sections

Author: Kaplan Test Prep

Publisher: Simon and Schuster

Published: 2024-12-03

Total Pages: 649

ISBN-13: 1506291023

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Kaplan's LSAT Logical Reasoning Prep is the single, most up-to-date resource you need to confidently answer logical reasoning questions on the LSAT, especially now that the logical reasoning sections are worth up to two-thirds of your entire score. The Law School Admissions Test, also known as the LSAT, underwent a dramatic test change in 2024. Inside this book are the insights of decades of LSAT expertise. Our world-leading faculty have used our decades of data to create in-depth strategies and tactics that catapult students to logical reasoning success. This comprehensive tool grants you access to the following resources. Fully compatible with the LSAT test maker's digital practice tool Official LSAT practice questions and practice exam A personal analysis of your strengths and weaknesses based on your official tests Expert strategies for every question type in the LR sections. Trips to improve timing and section management Dozens of skill-building drills and exercises Exclusive video strategy lessons and workshops from Kaplan’s LSAT top-rated faculty. Up-to-date for the Digital LSAT exam In-depth test-taking strategies to help you score higher We are so certain that LSAT Logical Reasoning Prep offers all the knowledge you need to excel in the logical reasoning section of the LSAT that we guarantee it: After studying with the online resources and book, you'll score higher on the LSAT—or you'll get your money back. The Best Review Kaplan’s LSAT experts share practical tips for using LSAC’s popular digital practice tool and the most widely used free online resources. Study plans will help you make the most of your practice time, regardless of how much time that is. Our exclusive data-driven learning strategies help you focus on what you need to study. In the online resources, an official full-length exam from LSAC, the LSAT testmaker, will help you feel comfortable with the exam format and avoid surprises on Test Day. Hundreds of real LSAT questions with detailed explanations Interactive online instructor-led workshops for expert review Online test analytics that analyzes your performance by section and question type Expert Guidance LSAT Logical Reasoning Prep includes access to lessons from Kaplan's award-winning LSAT Channel, which features one of its top LSAT teachers. We know the test: Kaplan's expert LSAT faculty teach the world's most popular LSAT course, and more people get into law school with a Kaplan LSAT course than all other major test prep companies combined. Kaplan's experts ensure our practice questions and study materials are true to the test. We invented test prep—Kaplan (www.kaptest.com) has been helping students for 80 years. Our proven strategies have helped legions of students achieve their dreams. Publisher's Note: Products purchased from 3rd party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entities included with the product.


Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery in Databases

Author: Ulf Brefeld

Publisher: Springer

Published: 2019-01-17

Total Pages: 724

ISBN-13: 3030109976

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The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learning; ensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.


A Practical Introduction to Health Information Management

A Practical Introduction to Health Information Management

Author: Lisa T. Johns

Publisher: Jones & Bartlett Learning

Published: 1998

Total Pages: 340

ISBN-13: 9780834212312

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Introducing the best one-step source of practical health information management guidance. In this text your students will find information they need to know for every key area of health information management -- information management standards and requirements ... clinical data systems ... computerized patient records ... confidentiality and security issues ... quality improvement ... telemedicine, people management issues ... and much more!


Introduction to Machine Learning

Introduction to Machine Learning

Author: Yves Kodratoff

Publisher: Elsevier

Published: 2014-06-28

Total Pages: 305

ISBN-13: 0080509304

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A textbook suitable for undergraduate courses in machine learningand related topics, this book provides a broad survey of the field.Generous exercises and examples give students a firm grasp of theconcepts and techniques of this rapidly developing, challenging subject. Introduction to Machine Learning synthesizes and clarifiesthe work of leading researchers, much of which is otherwise availableonly in undigested technical reports, journals, and conference proceedings.Beginning with an overview suitable for undergraduate readers, Kodratoffestablishes a theoretical basis for machine learning and describesits technical concepts and major application areas. Relevant logicprogramming examples are given in Prolog. Introduction to Machine Learning is an accessible and originalintroduction to a significant research area.