Cart

Unlocking potential with the best learning and research solutions

Look Inside Statistical Machine Translation

Statistical Machine Translation

Name: Statistical Machine Translation
Price: 87.99 USD
Availability: LimitedAvailability
ISBN: 9780511687594

$87.99 ( ) USD

textbook

Author: Philipp Koehn, University of Edinburgh

Date Published: June 2010
availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
format: Adobe eBook Reader
isbn: 9780511687594

Find out more about Cambridge eBooks

Rate & review

$ 87.99 USD ( )
Adobe eBook Reader

You will be taken to ebooks.com for this purchase

Buy eBook Add to wishlist

Other available formats:
Hardback

Looking for an examination copy?

If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact [email protected] providing details of the course you are teaching.

Description

Contents

Resources

Courses

About the Authors

This introductory text to statistical machine translation (SMT) provides all of the theories and methods needed to build a statistical machine translator, such as Google Language Tools and Babelfish. In general, statistical techniques allow automatic translation systems to be built quickly for any language-pair using only translated texts and generic software. With increasing globalization, statistical machine translation will be central to communication and commerce. Based on courses and tutorials, and classroom-tested globally, it is ideal for instruction or self-study, for advanced undergraduates and graduate students in computer science and/or computational linguistics, and researchers in natural language processing. The companion website provides open-source corpora and tool-kits.
- The first introductory guide to this burgeoning field - takes readers step by step through theory and methods
- Class tested by the author at universities and conference tutorials
- Accompanying website provides additional exercises and links to further resources
Read more
Reviews & endorsements
"Philipp Koehn has provided the first comprehensive text for this rapidly growing field of statistical machine translation. This book is an invaluable resource for students, researcher, and software developers, providing a lucid and detailed presentation of all the important ideas needed to understand or create a state-of-the-art statistical machine translation system."
Robert C. Moore, Microsoft Research
"This is an excellent introduction for someone interested in statistical translation. It is quite readable..."
Jeffrey Putnam, Computing Reviews
See more reviews
Customer reviews

Not yet reviewed
Be the first to review

Log in to review

Review was not posted due to profanity
×

, create a review

(If you're not , sign out)

Please enter the right captcha value

Please enter a star rating.

Your review must be a minimum of 12 words.

How do you rate this item?

Reviews must contain at least 12 words about the product.

×

Product details
- Date Published: June 2010
- format: Adobe eBook Reader
- isbn: 9780511687594
- contains: 24 b/w illus. 70 exercises
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
Preface
Part I. Foundations:
1. Introduction
2. Words, sentences, corpora
3. Probability theory
Part II. Core Methods:
4. Word-based models
5. Phrase-based models
6. Decoding
7. Language models
8. Evaluation
Part III. Advanced Topics:
9. Discriminative training
10. Integrating linguistic information
11. Tree-based models
Bibliography
Author index
Index.
Look Inside

General Resources

Resources

Find resources associated with this title

Back to resources home

Type	Name	Unlocked *	Format	Size

Showing of

This title is supported by one or more locked resources. Access to locked resources is granted exclusively by Cambridge University Press to instructors whose faculty status has been verified. To gain access to locked resources, instructors should sign in to or register for a Cambridge user account.

Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other instructors may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.

Supplementary resources are subject to copyright. Instructors are permitted to view, print or download these resources for use in their teaching, but may not change them or use them for commercial gain.

If you are having problems accessing these resources please contact [email protected].

Instructors have used or reviewed this title for the following courses
- Artificial Intelligence
- Language Engineering
- Machine Translation
- Natural Language Processing
- Natural Language Processing Techniques
- Statistical Machine Translation
- Statistical Natural Language Processing
Author
Philipp Koehn, University of Edinburgh
Philipp Koehn is a lecturer in the School of Informatics at the University of Edinburgh. He is the scientific co-ordinator of the European EuroMatrix project and also involved in research funded by DARPA in the USA. He has also collaborated with leading companies in the field, such as Systran and Asia Online. He implemented the widely used decoder Pharoah, and is leading the development of the open source machine translation toolkit Moses.