AI Assistants


AI Assistants (The MIT Press Essential Knowledge series)
Author: Roberto Pieraccini
Publisher Finelybook 出版社: MIT Press (7 Sept. 2021)
Language 语言: English
pages 页数: 288 pages
ISBN-10 书号: 0262542552
ISBN-13 书号: 9780262542555


Book Description
An accessible explanation of the technologies that enable such popular voice-interactive applications as Alexa,Siri,and Google Assistant.
Have you talked to a machine lately? Asked Alexa to play a song,asked Siri to call a friend,asked Google Assistant to make a shopping list? This volume in the MIT Press Essential Knowledge series offers a nontechnical and accessible explanation of the technologies that enable these popular devices. Roberto Pieraccini,drawing on more than thirty years of experience at companies including Bell Labs,IBM,and Google,describes the developments in such fields as artificial intelligence,machine learning,speech recognition,and natural language understanding that allow us to outsource tasks to our ubiquitous virtual assistants.
Pieraccini describes the software components that enable spoken communication between humans and computers,and explains why it’s so difficult to build machines that understand humans. He explains speech recognition technology; problems in extracting meaning from utterances in order to execute a request; language and speech generation; the dialog manager module; and interactions with social assistants and robots. Finally,he considers the next big challenge in the development of virtual assistants: building in more intelligence–enabling them to do more than communicate in natural language and endowing them with the capacity to know us better,predict our needs more accurately,and perform complex tasks with ease.

Table of contents:
Contents
Series Foreword
Preface
1: What Is a Virtual Assistant?
What Makes a Virtual Assistant
Why Spoken Language Communication with Machines Is Hard
2: AI and Machine Learning
Machine Learning
Statistical Machine Learning
Artificial Neural Networks
Deep Neural Networks
Recurrent Neural Networks
3: Speech Recognition
The Template Approach
Automated Typewriters
Automated Telephone Agents
Internet Speech2Text
Statistical Parametric Speech Recognition
End-to-End Speech Recognition
4: Natural Language Understanding
Meaning Representation
Statistical Natural Language Understanding
Deep Learning for Natural Language Understanding
Word Embeddings
NLU in Virtual Assistants
NLU Today
5: Natural Language and Speech Generation
Template-Based NLG
Back to Speech
6: The Dialog Manager
Dialog Manager Architecture
Interjections
Reinforcement Learning for Dialog
Deep Learning and Dialog
7: Interacting with an Assistant
Interaction Modalities
Social Virtual Assistants
8: Conclusions
Acknowledgments
Glossary
Notes
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Further Reading
Index

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