The dream of automatic language translation is now closer thanks to recent advances in the techniques that underpin statistical machine translation. This class-tested textbook from an active researcher in the field, provides a clear and careful introduction to the latest methods and explains how to build machine translation systems for any two languages. It introduces the subject's building blocks from linguistics and probability, then covers the major models for machine translation: word-based, phrase-based, and tree-based, as well as machine translation evaluation, language modeling, discriminative training and advanced methods to integrate linguistic annotation. The book also reports the latest research, presents the major outstanding challenges, and enables novices as well as experienced researchers to make novel contributions to this exciting area. Ideal for students at undergraduate and graduate level, or for anyone interested in the latest developments in machine translation.
具體描述
讀後感
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用戶評價
看哭瞭
评分語言學方麵還好，可是那些公式我實在看不明白。。。應該是不錯的書，但內容超齣瞭我的理解範圍。論文寫完就罷，不研究瞭。
评分SMT或SNLP研究者的必讀書！
评分語言學方麵還好，可是那些公式我實在看不明白。。。應該是不錯的書，但內容超齣瞭我的理解範圍。論文寫完就罷，不研究瞭。
评分語言學方麵還好，可是那些公式我實在看不明白。。。應該是不錯的書，但內容超齣瞭我的理解範圍。論文寫完就罷，不研究瞭。
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