1.2 History of Machine Translation
Chapter 2 Words, Sentences, Corpora
Chapter 3 Probability Theory
3.1 Estimating Probability Distributions
3.2 Calculating Probability Distributions
3.3 Properties of Probability Distributions
Chapter 4 Word-Based Models
4.1 Machine Translation by Translating Words
4.2 Learning Lexical Translation Models
4.3 Ensuring Fluent Output
Chapter 5 Phrase-Based Models
5.2 Learning a Phrase Translation Table
5.3 Extensions to the Translation Model
5.4 Extensions to the Reordering Model
5.5 EM Training of Phrase-Based Models
6.3 Future Cost Estimation
6.4 Other Decoding Algorithms
Chapter 7 Language Models
7.1 N-Gram Language Models
7.3 Interpolation and Back-off
7.4 Managing the Size of the Model
8.4 Task-Oriented Evaluation
Chapter 9 Discriminative Training
9.1 Finding Candidate Translations
9.2 Principles of Discriminative Methods
9.4 Large-Scale Discriminative Training
9.5 Posterior Methods and System Combination
Chapter 10 Integrating Linguistic Information
10.3 Syntactic Restructuring
10.5 Factored Translation Models
Chapter 11 Tree-Based Models
11.1 Synchronous Grammars
11.2 Learning Synchronous Grammars
