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Toy-MT-Introduction
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NiuTrans
Toy-MT-Introduction
Commits
207e0648
Commit
207e0648
authored
May 04, 2020
by
xiaotong
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updates of the content figure
parent
3d106c96
隐藏空白字符变更
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正在显示
5 个修改的文件
包含
116 行增加
和
797 行删除
+116
-797
Book/ChapterPreface/ChapterPreface.tex
+6
-5
Book/ChapterPreface/Figures/figure-preface.tex
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Book/mt-book-xelatex.idx
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Book/mt-book-xelatex.ptc
+68
-642
Book/mt-book-xelatex.tex
+1
-1
没有找到文件。
Book/ChapterPreface/ChapterPreface.tex
查看文件 @
207e0648
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@@ -14,11 +14,11 @@
\end{center}
\end{center}
\vspace
{
2em
}
\vspace
{
2em
}
\begin{spacing}
{
1.
4
}
\begin{spacing}
{
1.
2
}
让计算机进行自然语言的翻译是人类长期的梦想，也是人工智能的终极目标之一。自上世纪九十年代起，机器翻译也迈入了基于统计建模的时代，而发展到今天，深度学习等机器学习方法已经在机器翻译中得到了大量的应用，取得了令人瞩目的进步。
让计算机进行自然语言的翻译是人类长期的梦想，也是人工智能的终极目标之一。自上世纪九十年代起，机器翻译也迈入了基于统计建模的时代，而发展到今天，深度学习等机器学习方法已经在机器翻译中得到了大量的应用，取得了令人瞩目的进步。
在这个时代背景下，对机器翻译的模型、方法、实现技术进行深入了解是自然语言处理领域研究者和实践者所渴望的。本书全面的回顾了近三十年内机器翻译的技术发展历程，并围绕统计建模和深度学习两个主题对机器翻译的技术方法进行了全面介绍。在写作中，笔者力求用朴实的语言和
图画
阐述机器翻译的基本思想，同时对相关的技术前沿进行讨论。本书可以供计算机相关专业高年级本科生及研究生学习之用，也可以作为自然语言处理，特别是机器翻译相关研究人员的参考资料。
在这个时代背景下，对机器翻译的模型、方法、实现技术进行深入了解是自然语言处理领域研究者和实践者所渴望的。本书全面的回顾了近三十年内机器翻译的技术发展历程，并围绕统计建模和深度学习两个主题对机器翻译的技术方法进行了全面介绍。在写作中，笔者力求用朴实的语言和
实例
阐述机器翻译的基本思想，同时对相关的技术前沿进行讨论。本书可以供计算机相关专业高年级本科生及研究生学习之用，也可以作为自然语言处理，特别是机器翻译相关研究人员的参考资料。
本书共分为七个章节。章节的顺序参考了机器翻译技术发展的时间脉络，同时兼顾形成机器翻译知识体系的内在逻辑。各章节的主要内容包括：
本书共分为七个章节。章节的顺序参考了机器翻译技术发展的时间脉络，同时兼顾形成机器翻译知识体系的内在逻辑。各章节的主要内容包括：
...
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\vspace
{
0.4em
}
\vspace
{
0.4em
}
\end{itemize}
\end{itemize}
其中，第一章是对机器翻译的整体介绍。第二章和第五章是对统计建模和深度学习方法的介绍，分别建立了两个机器翻译范式的基础知识体系
\ \dash
\
统计机器翻译和神经机器翻译。统计机器翻译部分（第三、四章）涉及早期的基于单词的翻译模型，以及本世纪初流行的基于短语和句法的翻译模型；神经机器翻译（第六、七章）代表了
机器翻译的技术前沿，内容主要涉及了基于端到端表示学习的机器翻译建模方法。特别在第七章，本书对构建先进神经机器翻译的技术进行了较为全面的介绍
，为相关相关科学问题的研究和实用系统的开发提供了可落地的思路。图
\ref
{
fig:preface
}
展示了本书各个章节及核心概念之间的关系。
其中，第一章是对机器翻译的整体介绍。第二章和第五章是对统计建模和深度学习方法的介绍，分别建立了两个机器翻译范式的基础知识体系
\ \dash
\
统计机器翻译和神经机器翻译。统计机器翻译部分（第三、四章）涉及早期的基于单词的翻译模型，以及本世纪初流行的基于短语和句法的翻译模型；神经机器翻译（第六、七章）代表了
当今机器翻译的前沿，内容主要涉及了基于端到端表示学习的机器翻译建模方法。特别是，第七章对一些先进的神经机器翻译方法进行了讨论
，为相关相关科学问题的研究和实用系统的开发提供了可落地的思路。图
\ref
{
fig:preface
}
展示了本书各个章节及核心概念之间的关系。
{
\red
用最简单的方式阐述机器翻译的基本思想
}
是笔者所期望达到的
。但是，书中难免会涉及一些概念形式化定义和算法的抽象描述，笔者也都尽所能通过图形进行解释
。不过，本书所包含的内容较为广泛，难免有疏漏之处，望读者海涵，并指出不当之处。
{
\red
用最简单的方式阐述机器翻译的基本思想
}
是笔者所期望达到的
目标。但是，书中难免会涉及一些概念形式化定义和算法的抽象描述，笔者也都尽所能通过图例进行解释（本书共320张插图）
。不过，本书所包含的内容较为广泛，难免有疏漏之处，望读者海涵，并指出不当之处。
\begin{figure}
[htp]
\begin{figure}
[htp]
\centering
\centering
%\includegraphics[scale=0.36]{./Chapter6/Figures/mt-history.png}
\centering
\input
{
./ChapterPreface/Figures/figure-preface
}
\caption
{
本书各章节及核心概念关系图
}
\caption
{
本书各章节及核心概念关系图
}
\label
{
fig:preface
}
\label
{
fig:preface
}
\end{figure}
\end{figure}
...
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Book/ChapterPreface/Figures/figure-preface.tex
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查看文件 @
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Book/mt-book-xelatex.idx
查看文件 @
207e0648
\indexentry{未登录词|hyperpage}{13}
\indexentry{Out of Vocabulary Word，OOV Word|hyperpage}{13}
\indexentry{子词切分|hyperpage}{13}
\indexentry{Sub-word Segmentation|hyperpage}{13}
\indexentry{标准化|hyperpage}{13}
\indexentry{Normalization|hyperpage}{13}
\indexentry{数据清洗|hyperpage}{13}
\indexentry{Dada Cleaning|hyperpage}{13}
\indexentry{数据选择|hyperpage}{15}
\indexentry{Data Selection|hyperpage}{15}
\indexentry{数据过滤|hyperpage}{15}
\indexentry{Data Filtering|hyperpage}{15}
\indexentry{开放词表|hyperpage}{18}
\indexentry{Open-Vocabulary|hyperpage}{18}
\indexentry{子词|hyperpage}{19}
\indexentry{Sub-word|hyperpage}{19}
\indexentry{字节对编码|hyperpage}{19}
\indexentry{双字节编码|hyperpage}{19}
\indexentry{Byte Pair Encoding，BPE|hyperpage}{19}
\indexentry{正则化|hyperpage}{22}
\indexentry{Regularization|hyperpage}{22}
\indexentry{过拟合问题|hyperpage}{22}
\indexentry{Overfitting Problem|hyperpage}{22}
\indexentry{反问题|hyperpage}{22}
\indexentry{Inverse Problem|hyperpage}{22}
\indexentry{适定的|hyperpage}{22}
\indexentry{Well-posed|hyperpage}{22}
\indexentry{不适定问题|hyperpage}{22}
\indexentry{Ill-posed Problem|hyperpage}{22}
\indexentry{降噪|hyperpage}{23}
\indexentry{Denoising|hyperpage}{23}
\indexentry{泛化|hyperpage}{23}
\indexentry{Generalization|hyperpage}{23}
\indexentry{标签平滑|hyperpage}{25}
\indexentry{Label Smoothing|hyperpage}{25}
\indexentry{相互适应|hyperpage}{26}
\indexentry{Co-Adaptation|hyperpage}{26}
\indexentry{集成学习|hyperpage}{27}
\indexentry{Ensemble Learning|hyperpage}{27}
\indexentry{容量|hyperpage}{28}
\indexentry{Capacity|hyperpage}{28}
\indexentry{宽残差网络|hyperpage}{29}
\indexentry{Wide Residual Network|hyperpage}{29}
\indexentry{探测任务|hyperpage}{30}
\indexentry{Probing Task|hyperpage}{30}
\indexentry{表面信息|hyperpage}{30}
\indexentry{Surface Information|hyperpage}{30}
\indexentry{语法信息|hyperpage}{30}
\indexentry{Syntactic Information|hyperpage}{30}
\indexentry{语义信息|hyperpage}{30}
\indexentry{Semantic Information|hyperpage}{30}
\indexentry{词嵌入|hyperpage}{31}
\indexentry{Embedding|hyperpage}{31}
\indexentry{数据并行|hyperpage}{31}
\indexentry{Data Parallelism|hyperpage}{31}
\indexentry{模型并行|hyperpage}{31}
\indexentry{Model Parallelism|hyperpage}{31}
\indexentry{小批量训练|hyperpage}{31}
\indexentry{Mini-batch Training|hyperpage}{31}
\indexentry{课程学习|hyperpage}{33}
\indexentry{Curriculum Learning|hyperpage}{33}
\indexentry{推断|hyperpage}{34}
\indexentry{Inference|hyperpage}{34}
\indexentry{解码|hyperpage}{34}
\indexentry{Decoding|hyperpage}{34}
\indexentry{搜索错误|hyperpage}{34}
\indexentry{Search Error|hyperpage}{34}
\indexentry{模型错误|hyperpage}{34}
\indexentry{Modeling Error|hyperpage}{34}
\indexentry{重排序|hyperpage}{36}
\indexentry{Re-ranking|hyperpage}{36}
\indexentry{双向推断|hyperpage}{36}
\indexentry{Bidirectional Inference|hyperpage}{36}
\indexentry{批量推断|hyperpage}{40}
\indexentry{Batch Inference|hyperpage}{40}
\indexentry{批量处理|hyperpage}{40}
\indexentry{Batching|hyperpage}{40}
\indexentry{二值网络|hyperpage}{41}
\indexentry{Binarized Neural Networks|hyperpage}{41}
\indexentry{自回归翻译|hyperpage}{42}
\indexentry{Autoregressive Translation|hyperpage}{42}
\indexentry{非自回归翻译|hyperpage}{42}
\indexentry{Regressive Translation|hyperpage}{42}
\indexentry{繁衍率|hyperpage}{42}
\indexentry{Fertility|hyperpage}{42}
\indexentry{偏置|hyperpage}{43}
\indexentry{Bias|hyperpage}{43}
\indexentry{退化|hyperpage}{44}
\indexentry{Degenerate|hyperpage}{44}
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\indexentry{Over Translation|hyperpage}{45}
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\indexentry{充分性|hyperpage}{46}
\indexentry{Adequacy|hyperpage}{46}
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\indexentry{混淆网络|hyperpage}{49}
\indexentry{Confusion Network|hyperpage}{49}
\indexentry{动态线性层聚合方法|hyperpage}{53}
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\indexentry{相互适应|hyperpage}{57}
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\indexentry{Data Augmentation|hyperpage}{59}
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\indexentry{Back Translation|hyperpage}{59}
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\indexentry{分布式表示|hyperpage}{61}
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\indexentry{Pre-training|hyperpage}{61}
\indexentry{微调|hyperpage}{61}
\indexentry{Fine-tuning|hyperpage}{61}
\indexentry{多任务学习|hyperpage}{63}
\indexentry{Multitask Learning|hyperpage}{63}
\indexentry{知识精炼|hyperpage}{64}
\indexentry{Knowledge Distillation|hyperpage}{64}
\indexentry{模型压缩|hyperpage}{64}
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\indexentry{学习难度|hyperpage}{64}
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\indexentry{Teacher Model|hyperpage}{65}
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\indexentry{Hint-based Knowledge Transfer|hyperpage}{66}
\indexentry{注意力分布|hyperpage}{66}
\indexentry{Attention To Attention Transfer|hyperpage}{67}
\indexentry{循环一致性|hyperpage}{69}
\indexentry{Circle Consistency|hyperpage}{69}
\indexentry{翻译中回译|hyperpage}{70}
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\indexentry{神经架构搜索|hyperpage}{73}
\indexentry{Neural Architecture Search|hyperpage}{73}
Book/mt-book-xelatex.ptc
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机器翻译基础}}{13
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%\include{Chapter4/chapter4}
%\include{Chapter4/chapter4}
%\include{Chapter5/chapter5}
%\include{Chapter5/chapter5}
%\include{Chapter6/chapter6}
%\include{Chapter6/chapter6}
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{
Chapter7/chapter7
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\include{Chapter7/chapter7}
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