Machine Translation (Hardcover)

Three paradigms have dominated machine translation (MT)—rule-based machine translation (RBMT), statistical machine translation (SMT), and example-based machine translation (EBMT). These paradigms differ in the way they handle the three fundamental processes in MT—analysis, transfer, and generation (ATG). In its pure form, RBMT uses rules, while SMT uses data. EBMT tries a combination—data supplies translation parts that rules recombine to produce translation.

Machine Translation compares and contrasts the salient principles and practices of RBMT, SMT, and EBMT. Offering an exposition of language phenomena followed by modeling and experimentation, the text:

• Introduces MT against the backdrop of language divergence and the Vauquois triangle
• Presents expectation maximization (EM)-based word alignment as a turning point in the history of MT
• Discusses the most important element of SMT—bilingual word alignment from pairs of parallel translations
• Explores the IBM models of MT, explaining how to find the best alignment given a translation pair and how to find the best translation given a new input sentence
• Covers the mathematics of phrase-based SMT, phrase-based decoding, and the Moses SMT environment
• Provides complete walk-throughs of the working of interlingua-based and transfer-based RBMT
• Analyzes EBMT, showing how translation parts can be extracted and recombined to translate a new input, all automatically
• Includes numerous examples that illustrate universal translation phenomena through the usage of specific languages

Machine Translation is designed for advanced undergraduate-level and graduate-level courses in machine translation and natural language processing. The book also makes a handy professional reference for computer engineers.

機器翻譯（MT）有三種主要範式：基於規則的機器翻譯（RBMT）、統計機器翻譯（SMT）和基於範例的機器翻譯（EBMT）。這些範式在處理機器翻譯的三個基本過程（分析、轉換和生成）方面有所不同。在純粹的形式下，RBMT使用規則，而SMT使用數據。EBMT則嘗試結合兩者，使用數據提供翻譯部分，然後使用規則重新組合以生成翻譯。

《機器翻譯》比較和對比了RBMT、SMT和EBMT的重要原則和實踐。通過對語言現象的闡述、建模和實驗，本書：

- 在語言差異和Vauquois三角背景下介紹了機器翻譯
- 將基於期望最大化（EM）的詞對齊作為機器翻譯歷史上的轉折點
- 討論了SMT中最重要的元素——從平行翻譯對中進行雙語詞對齊
- 探討了IBM模型的機器翻譯，解釋如何在給定翻譯對的情況下找到最佳對齊，以及如何在給定新輸入句子的情況下找到最佳翻譯
- 詳細介紹了基於片語的SMT的數學原理、片語解碼和Moses SMT環境
- 提供了基於內部語和基於轉換的RBMT的完整操作示例
- 分析了EBMT，展示了如何自動提取和重新組合翻譯部分以翻譯新的輸入
- 通過具體語言的使用示例，說明了普遍的翻譯現象

《機器翻譯》適用於高年級本科和研究生課程，包括機器翻譯和自然語言處理。本書也是計算機工程師的實用專業參考資料。