This is a tutorial, the purpose is to introduce the basic knowledge and modeling methods of machine translation systematically, and on this basis, discuss some cutting-edge technologies of machine translation (formerly known as "Machine Translation: Statistical Modeling and Deep Learning") method"). Its content is compiled into a book, which can be used for the study of senior undergraduates and graduate students in computer and artificial intelligence related majors, and can also be used as reference material for researchers related to natural language processing, especially machine translation. This book is written in tex, and all source codes are open. This book is divided into four parts, each of which consists of several chapters. The order of the chapters refers to the time context of the development of machine translation technology, while taking into account the internal logic of the machine translation knowledge system.

Features

  • Statistical Language Modeling Fundamentals
  • Lexical Analysis and Syntax Analysis Fundamentals
  • Translation quality evaluation
  • Word-Based Machine Translation Modeling
  • Models based on torsion and fecundity
  • Artificial Neural Networks and Neural Language Modeling

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Operating Systems

Linux, Mac, Windows

Registered

2022-08-08