Description: Automatic Speech Recognition by Kai-Fu Lee Speech Recognition has a long history of being one of the difficult problems in Artificial Intelligence and Computer Science. These include cost, real time response, speaker independence, robustness to variations such as noise, microphone, speech rate and loudness, and the ability to handle non-grammatical speech. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description Speech Recognition has a long history of being one of the difficult problems in Artificial Intelligence and Computer Science. As one goes from problem solving tasks such as puzzles and chess to perceptual tasks such as speech and vision, the problem characteristics change dramatically: knowledge poor to knowledge rich; low data rates to high data rates; slow response time (minutes to hours) to instantaneous response time. These characteristics taken together increase the computational complexity of the problem by several orders of magnitude. Further, speech provides a challenging task domain which embodies many of the requirements of intelligent behavior: operate in real time; exploit vast amounts of knowledge, tolerate errorful, unexpected unknown input; use symbols and abstractions; communicate in natural language and learn from the environment. Voice input to computers offers a number of advantages. It provides a natural, fast, hands free, eyes free, location free input medium. However, there are many as yet unsolved problems that prevent routine use of speech as an input device by non-experts. These include cost, real time response, speaker independence, robustness to variations such as noise, microphone, speech rate and loudness, and the ability to handle non-grammatical speech. Satisfactory solutions to each of these problems can be expected within the next decade. Recognition of unrestricted spontaneous continuous speech appears unsolvable at present. However, by the addition of simple constraints, such as clarification dialog to resolve ambiguity, we believe it will be possible to develop systems capable of accepting very large vocabulary continuous speechdictation. Table of Contents 1. Introduction.- 2. Hidden Markov Modeling of Speech.- 3. Task and Databases.- 4. The Baseline SPHINX System.- 5. Adding Knowledge.- 6. Finding a Good Unit of Speech.- 7. Learning and Adaptation.- 8. Summary of Results.- 9. Conclusion.- Appendix I. Evaluating Speech Recognizers.- I.1. Perplexity.- I.2. Computing Error Rate.- Appendix H. The Resource Management Task.- II.1. The Vocabulary and the SPHINX Pronunciation Dictionary.- II.2. The Grammar.- II.3. Training and Test Speakers.- Appendix III. Examples of SPHINX Recognition.- References. Promotional Springer Book Archives Long Description Speech Recognition has a long history of being one of the difficult problems in Artificial Intelligence and Computer Science. As one goes from problem solving tasks such as puzzles and chess to perceptual tasks such as speech and vision, the problem characteristics change dramatically: knowledge poor to knowledge rich; low data rates to high data rates; slow response time (minutes to hours) to instantaneous response time. These characteristics taken together increase the computational complexity of the problem by several orders of magnitude. Further, speech provides a challenging task domain which embodies many of the requirements of intelligent behavior: operate in real time; exploit vast amounts of knowledge, tolerate errorful, unexpected unknown input; use symbols and abstractions; communicate in natural language and learn from the environment. Voice input to computers offers a number of advantages. It provides a natural, fast, hands free, eyes free, location free input medium. However, there are many as yet unsolved problems that prevent routine use of speech as an input device by non-experts. These include cost, real time response, speaker independence, robustness to variations such as noise, microphone, speech rate and loudness, and the ability to handle non-grammatical speech. Satisfactory solutions to each of these problems can be expected within the next decade. Recognition of unrestricted spontaneous continuous speech appears unsolvable at present. However, by the addition of simple constraints, such as clarification dialog to resolve ambiguity, we believe it will be possible to develop systems capable of accepting very large vocabulary continuous speechdictation. Details ISBN1461366240 Language English Edition 88199th ISBN-10 1461366240 ISBN-13 9781461366249 Media Book DEWEY 006.454 Series Number 62 Year 2013 Publication Date 2013-03-03 Imprint Springer-Verlag New York Inc. Place of Publication New York, NY Country of Publication United States Short Title AUTOMATIC SPEECH RECOGNITION 1 Illustrations XV, 207 p. AU Release Date 2013-03-03 NZ Release Date 2013-03-03 US Release Date 2013-03-03 UK Release Date 2013-03-03 Author Kai-Fu Lee Pages 207 Publisher Springer-Verlag New York Inc. Edition Description Softcover reprint of the original 1st ed. 1989 Series The Springer International Series in Engineering and Computer Science Format Paperback Subtitle The Development of the SPHINX System Alternative 9780898382969 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:96342509;
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ISBN-13: 9781461366249
Book Title: Automatic Speech Recognition
Number of Pages: 207 Pages
Language: English
Publication Name: Automatic Speech Recognition: the Development of the Sphinx System
Publisher: Springer-Verlag New York Inc.
Publication Year: 2013
Subject: Engineering & Technology, Computer Science
Item Height: 235 mm
Item Weight: 355 g
Type: Textbook
Author: Kai-Fu Lee
Item Width: 155 mm
Format: Paperback
