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mtbookv2
Commits
35e52982
Commit
35e52982
authored
Jan 09, 2021
by
孟霞
Browse files
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Plain Diff
合并分支 'master' 到 'mengxia'
Master 查看合并请求
!831
parents
b354a1a2
9fcf1074
全部展开
隐藏空白字符变更
内嵌
并排
正在显示
23 个修改的文件
包含
98 行增加
和
97 行删除
+98
-97
Chapter13/Figures/figure-bpe.tex
+4
-4
Chapter13/Figures/figure-framework-of-Adversarial-Neural-machine-translation.tex
+1
-1
Chapter14/Figures/figure-different-integration-model.tex
+11
-11
Chapter14/Figures/figure-hypothesis-generation.tex
+8
-8
Chapter14/Figures/figure-main-module.tex
+2
-2
Chapter14/Figures/figure-multi-modality.tex
+3
-3
Chapter14/Figures/figure-non-autoregressive.tex
+5
-5
Chapter15/Figures/figure-encoder-of-bidirectional-tree-structure.tex
+10
-10
Chapter15/Figures/figure-encoder-tree-structure-modeling.tex
+5
-5
Chapter15/Figures/figure-layer-fusion-method.tex
+4
-4
Chapter15/Figures/figure-main-flow-of-neural-network-structure-search.tex
+3
-3
Chapter15/Figures/figure-multi-task-structure.tex
+1
-1
Chapter15/Figures/figure-structure-search-based-on-gradient-method.tex
+1
-1
Chapter15/Figures/figure-structure-search-based-on-reinforcement-learning.tex
+1
-1
Chapter15/Figures/figure-three-fusion-methods-of-tree-structure-information-1.tex
+2
-2
Chapter15/Figures/figure-three-fusion-methods-of-tree-structure-information-2.tex
+5
-5
Chapter15/chapter15.tex
+0
-0
Chapter16/Figures/figure-shared-space-inductive-bilingual-dictionary.tex
+10
-10
Chapter16/chapter16.tex
+0
-0
Chapter17/Figures/figure-cache.tex
+13
-12
Chapter17/chapter17.tex
+7
-7
Chapter8/chapter8.tex
+2
-2
ChapterAppend/chapterappend.tex
+0
-0
没有找到文件。
Chapter13/Figures/figure-bpe.tex
查看文件 @
35e52982
\begin{tikzpicture}
\tikzstyle
{
tnode
}
= [rectangle,inner sep=0em,minimum width=8em,minimum height=6.6em,rounded corners=5pt,fill=
u
green!20]
\tikzstyle
{
pnode
}
= [rectangle,inner sep=0em,minimum width=8em,minimum height=6.6em,rounded corners=5pt,fill=yellow!
2
0]
\tikzstyle
{
tnode
}
= [rectangle,inner sep=0em,minimum width=8em,minimum height=6.6em,rounded corners=5pt,fill=green!20]
\tikzstyle
{
pnode
}
= [rectangle,inner sep=0em,minimum width=8em,minimum height=6.6em,rounded corners=5pt,fill=yellow!
3
0]
\tikzstyle
{
mnode
}
= [rectangle,inner sep=0em,minimum width=8em,minimum height=6.6em,rounded corners=5pt,fill=red!20]
\tikzstyle
{
wnode
}
= [inner sep=0em,minimum height=1.5em]
...
...
@@ -19,7 +19,7 @@
\begin{pgfonlayer}
{
background
}
\node
[rectangle,inner sep=0.7em,draw,ugreen!
4
0,dashed,very thick,rounded corners=7pt] [fit = (n1) (n4)] (box1)
{}
;
\node
[rectangle,inner sep=0.7em,draw,ugreen!
6
0,dashed,very thick,rounded corners=7pt] [fit = (n1) (n4)] (box1)
{}
;
\end{pgfonlayer}
\node
[anchor=west,align=left,font=
\footnotesize
] (nt1) at ([xshift=0.1em,yshift=0em]n2.east)
{
统计词表和
\\
[0.5ex]
词频
}
;
...
...
@@ -75,7 +75,7 @@
\node
[anchor=east,ublue,align=left,font=
\footnotesize
] (l3) at ([xshift=-0.5em,yshift=0em]cd.west)
{
直至达到设定的符号合
\\
并表大小或无法合并
}
;
\begin{pgfonlayer}
{
background
}
\node
[rectangle,inner sep=0.7em,draw,
yellow
!40,dashed,very thick,rounded corners=7pt] [fit = (n5) (n8) (l3) (cd)] (box2)
{}
;
\node
[rectangle,inner sep=0.7em,draw,
orange
!40,dashed,very thick,rounded corners=7pt] [fit = (n5) (n8) (l3) (cd)] (box2)
{}
;
\end{pgfonlayer}
%第五排
...
...
Chapter13/Figures/figure-framework-of-Adversarial-Neural-machine-translation.tex
查看文件 @
35e52982
...
...
@@ -4,7 +4,7 @@
\begin{tikzpicture}
\tikzstyle
{
rnnnode
}
= [draw,inner sep=4pt,minimum width=2em,minimum height=2em,rounded corners=1pt,fill=
yellow
!20]
\tikzstyle
{
rnnnode
}
= [draw,inner sep=4pt,minimum width=2em,minimum height=2em,rounded corners=1pt,fill=
green
!20]
\tikzstyle
{
snode
}
= [draw,inner sep=4pt,minimum width=2em,minimum height=2em,rounded corners=1pt,fill=red!20]
\tikzstyle
{
wode
}
= [inner sep=0pt,minimum width=2em,minimum height=2em,rounded corners=0pt]
...
...
Chapter14/Figures/figure-different-integration-model.tex
查看文件 @
35e52982
...
...
@@ -10,12 +10,12 @@
\tikzstyle
{
output
}
= [rectangle,thick,rounded corners=3pt,minimum width=1.2cm,align=center,font=
\scriptsize
];
\begin{scope}
\node
[system,fill=
orange!2
0,draw] (model3) at (0,0)
{
模型
$
3
$}
;
\node
[system,fill=
u
green!20,draw,anchor=south] (model2) at ([yshift=0.5cm]model3.north)
{
模型
$
2
$}
;
\node
[system,fill=
yellow!3
0,draw] (model3) at (0,0)
{
模型
$
3
$}
;
\node
[system,fill=green!20,draw,anchor=south] (model2) at ([yshift=0.5cm]model3.north)
{
模型
$
2
$}
;
\node
[system,fill=red!20,draw,anchor=south] (model1) at ([yshift=0.5cm]model2.north)
{
模型
$
1
$}
;
\node
[output,fill=
orange!2
0,draw,anchor=west] (output3) at ([xshift=0.8cm]model3.east)
{
输出
$
3
$}
;
\node
[output,fill=
u
green!20,draw,anchor=west] (output2) at ([xshift=0.8cm]model2.east)
{
输出
$
2
$}
;
\node
[output,fill=
yellow!3
0,draw,anchor=west] (output3) at ([xshift=0.8cm]model3.east)
{
输出
$
3
$}
;
\node
[output,fill=green!20,draw,anchor=west] (output2) at ([xshift=0.8cm]model2.east)
{
输出
$
2
$}
;
\node
[output,fill=red!20,draw,anchor=west] (output1) at ([xshift=0.8cm]model1.east)
{
输出
$
1
$}
;
\begin{pgfonlayer}
{
background
}
...
...
@@ -40,15 +40,15 @@
\tikzstyle
{
output
}
= [rectangle,thick,rounded corners=3pt,minimum width=1.2cm,align=center,font=
\scriptsize
];
\begin{scope}
\node
[system,fill=
orange!2
0,draw] (model3) at (0,0)
{
模型
$
3
$}
;
\node
[system,fill=
u
green!20,draw,anchor=south] (model2) at ([yshift=0.5cm]model3.north)
{
模型
$
2
$}
;
\node
[system,fill=
yellow!3
0,draw] (model3) at (0,0)
{
模型
$
3
$}
;
\node
[system,fill=green!20,draw,anchor=south] (model2) at ([yshift=0.5cm]model3.north)
{
模型
$
2
$}
;
\node
[system,fill=red!20,draw,anchor=south] (model1) at ([yshift=0.5cm]model2.north)
{
模型
$
1
$}
;
\begin{pgfonlayer}
{
background
}
\node
[draw,thick,dashed,inner sep=3pt,fit=(model3) (model2) (model1)] (ensemble)
{}
;
\end{pgfonlayer}
\node
[system,fill=
u
green!20,draw,right=1cm of ensemble] (model)
{
模型
}
;
\node
[system,fill=green!20,draw,right=1cm of ensemble] (model)
{
模型
}
;
\node
[output,fill=cocoabrown!20,draw,minimum width=1.2cm,anchor=west] (final) at ([xshift=0.8cm]model.east)
{
最终
\\
输出
}
;
...
...
@@ -68,12 +68,12 @@
\tikzstyle
{
dot
}
= [circle,fill=blue!40!white,minimum size=5pt,inner sep=0pt];
\begin{scope}
\node
[system,fill=
orange!2
0,draw] (model3) at (0,0)
{
模型
$
3
$}
;
\node
[system,fill=
u
green!20,draw,anchor=south] (model2) at ([yshift=0.5cm]model3.north)
{
模型
$
2
$}
;
\node
[system,fill=
yellow!3
0,draw] (model3) at (0,0)
{
模型
$
3
$}
;
\node
[system,fill=green!20,draw,anchor=south] (model2) at ([yshift=0.5cm]model3.north)
{
模型
$
2
$}
;
\node
[system,fill=red!20,draw,anchor=south] (model1) at ([yshift=0.5cm]model2.north)
{
模型
$
1
$}
;
\node
[output,fill=
orange!2
0,draw,anchor=west] (output3) at ([xshift=0.8cm]model3.east)
{
输出
$
3
$}
;
\node
[output,fill=
u
green!20,draw,anchor=west] (output2) at ([xshift=0.8cm]model2.east)
{
输出
$
2
$}
;
\node
[output,fill=
yellow!3
0,draw,anchor=west] (output3) at ([xshift=0.8cm]model3.east)
{
输出
$
3
$}
;
\node
[output,fill=green!20,draw,anchor=west] (output2) at ([xshift=0.8cm]model2.east)
{
输出
$
2
$}
;
\node
[output,fill=red!20,draw,anchor=west] (output1) at ([xshift=0.8cm]model1.east)
{
输出
$
1
$}
;
\draw
[->,very thick] (model1) to (output1);
...
...
Chapter14/Figures/figure-hypothesis-generation.tex
查看文件 @
35e52982
...
...
@@ -5,12 +5,12 @@
\tikzstyle
{
output
}
= [rectangle,thick,rounded corners=3pt,minimum width=1.2cm,align=center,font=
\scriptsize
];
\begin{scope}
[local bounding box=MULTIPLE]
\node
[system,fill=
orange!2
0,draw] (engine3) at (0,0)
{
系统
$
n
$}
;
\node
[system,fill=
u
green!20,draw,anchor=south] (engine2) at ([yshift=0.6cm]engine3.north)
{
系统
$
2
$}
;
\node
[system,fill=
yellow!3
0,draw] (engine3) at (0,0)
{
系统
$
n
$}
;
\node
[system,fill=green!20,draw,anchor=south] (engine2) at ([yshift=0.6cm]engine3.north)
{
系统
$
2
$}
;
\node
[system,fill=red!20,draw,anchor=south] (engine1) at ([yshift=0.3cm]engine2.north)
{
系统
$
1
$}
;
\node
[output,fill=
orange!2
0,draw,anchor=west] (output3) at ([xshift=0.5cm]engine3.east)
{
输出
$
n
$}
;
\node
[output,fill=
u
green!20,draw,anchor=west] (output2) at ([xshift=0.5cm]engine2.east)
{
输出
$
2
$}
;
\node
[output,fill=
yellow!3
0,draw,anchor=west] (output3) at ([xshift=0.5cm]engine3.east)
{
输出
$
n
$}
;
\node
[output,fill=green!20,draw,anchor=west] (output2) at ([xshift=0.5cm]engine2.east)
{
输出
$
2
$}
;
\node
[output,fill=red!20,draw,anchor=west] (output1) at ([xshift=0.5cm]engine1.east)
{
输出
$
1
$}
;
\draw
[very thick,decorate,decoration=
{
brace
}
] ([xshift=3pt]output1.north east) to node [midway,name=final]
{}
([xshift=3pt]output3.south east);
...
...
@@ -25,11 +25,11 @@
\end{scope}
\begin{scope}
[local bounding box=SINGLE]
\node
[output,fill=
u
green!20,draw,anchor=west] (output3) at ([xshift=4cm]output3.east)
{
输出
$
n
$}
;
\node
[output,fill=
u
green!20,draw,anchor=west] (output2) at ([xshift=4cm]output2.east)
{
输出
$
2
$}
;
\node
[output,fill=
u
green!20,draw,anchor=west] (output1) at ([xshift=4cm]output1.east)
{
输出
$
1
$}
;
\node
[output,fill=green!20,draw,anchor=west] (output3) at ([xshift=4cm]output3.east)
{
输出
$
n
$}
;
\node
[output,fill=green!20,draw,anchor=west] (output2) at ([xshift=4cm]output2.east)
{
输出
$
2
$}
;
\node
[output,fill=green!20,draw,anchor=west] (output1) at ([xshift=4cm]output1.east)
{
输出
$
1
$}
;
\node
[system,fill=
u
green!20,draw,anchor=east,align=center,inner sep=1.9pt] (engine) at ([xshift=-0.5cm]output2.west)
{
单系统
}
;
\node
[system,fill=green!20,draw,anchor=east,align=center,inner sep=1.9pt] (engine) at ([xshift=-0.5cm]output2.west)
{
单系统
}
;
\draw
[very thick,decorate,decoration=
{
brace
}
] ([xshift=3pt]output1.north east) to node [midway,name=final]
{}
([xshift=3pt]output3.south east);
...
...
Chapter14/Figures/figure-main-module.tex
查看文件 @
35e52982
\begin{tikzpicture}
%左
\node
[anchor=west,draw=black!70,rounded corners,drop shadow,very thick,minimum width=6em,minimum height=3.5em,fill=
blue!15,align=center,text=black] (part1) at (0,0)
{
\scriptsize
{
预测模块
}}
;
\node
[anchor=west,draw=black!70,rounded corners,drop shadow,very thick,minimum width=6em,minimum height=3.5em,fill=
red!15,align=center,text=black] (part1) at (0,0)
{
\small
{
预测模块
}}
;
\node
[anchor=south] (text) at ([xshift=0.5em,yshift=-3.5em]part1.south)
{
\scriptsize
{
源语言句子(编码器输出)
}}
;
\node
[anchor=east,draw=black!70,rounded corners,drop shadow,very thick,minimum width=6em,minimum height=3.5em,fill=
blue!15,align=center,text=black] (part2) at ([xshift=10em]part1.east)
{
\scriptsize
{
搜索模块
}}
;
\node
[anchor=east,draw=black!70,rounded corners,drop shadow,very thick,minimum width=6em,minimum height=3.5em,fill=
green!15,align=center,text=black] (part2) at ([xshift=10em]part1.east)
{
\small
{
搜索模块
}}
;
\node
[anchor=south] (text1) at ([xshift=0.1em,yshift=2.2em]part1.north)
{
\scriptsize
{
译文中已经生成的单词
}}
;
\node
[anchor=south] (text2) at ([xshift=0.5em,yshift=2.2em]part2.north)
{
\scriptsize
{
预测当前位置的单词概率分布
}}
;
...
...
Chapter14/Figures/figure-multi-modality.tex
查看文件 @
35e52982
...
...
@@ -8,10 +8,10 @@
\tikzstyle
{
po
}
= [font=
\scriptsize
,rounded corners=1pt, fill=gray!20, minimum width=1.8em,minimum height=1.5em,draw]
\tikzstyle
{
tgt
}
= [minimum height=1.6em,minimum width=5.2em,fill=black!10!yellow!30,font=
\footnotesize
,drop shadow=
{
shadow xshift=0.15em,shadow yshift=-0.15em,
}
]
\tikzstyle
{
p
}
= [fill=ugreen!15,minimum width=0.4em,inner sep=0pt]
\node
[ rounded corners=3pt, fill=red!20, drop shadow, minimum width=12em,minimum height=4em,draw]
(encoder) at (0,0)
{
编码器
}
;
\node
[anchor=north,rounded corners=3pt, fill=yellow!20, drop shadow, minimum width=12em,minimum height=2em,draw]
(lenpre) at([yshift=3em]encoder.north)
{
长度预测器
}
;
\node
[ rounded corners=3pt,
thick,
fill=red!20, drop shadow, minimum width=12em,minimum height=4em,draw]
(encoder) at (0,0)
{
编码器
}
;
\node
[anchor=north,rounded corners=3pt,
thick,
fill=yellow!20, drop shadow, minimum width=12em,minimum height=2em,draw]
(lenpre) at([yshift=3em]encoder.north)
{
长度预测器
}
;
\node
[anchor=north]
(lable) at([xshift=3.5em,yshift=2.5em]lenpre.north)
{
译文长度:3
}
;
\node
[anchor=west, rounded corners=3pt, fill=blue!20, drop shadow, minimum width=13em,minimum height=4em,draw]
(decoder) at ([xshift=1cm]encoder.east)
{
解码器
}
;
\node
[anchor=west, rounded corners=3pt,
thick,
fill=blue!20, drop shadow, minimum width=13em,minimum height=4em,draw]
(decoder) at ([xshift=1cm]encoder.east)
{
解码器
}
;
\node
[anchor=north,emb]
(en1) at ([yshift=-1.3em,xshift=-4.5em]encoder.south)
{${
\mathbi
e
}$
(干)
}
;
\node
[anchor=north,emb]
(en2) at ([yshift=-1.3em,xshift=-1.5em]encoder.south)
{${
\mathbi
e
}$
(得)
}
;
...
...
Chapter14/Figures/figure-non-autoregressive.tex
查看文件 @
35e52982
...
...
@@ -7,10 +7,10 @@
\tikzstyle
{
emb
}
= [font=
\scriptsize
,rounded corners=1pt, fill=orange!20, minimum width=1.8em,minimum height=1.5em,draw]
\tikzstyle
{
po
}
= [font=
\scriptsize
,rounded corners=1pt, fill=gray!20, minimum width=1.8em,minimum height=1.5em,draw]
\begin{scope}
\node
[rounded corners=3pt, fill=red!20, drop shadow, minimum width=10em,minimum height=4em,draw]
(encoder) at (0,0)
{
编码器
}
;
\node
[anchor=north,rounded corners=3pt, fill=yellow!20, drop shadow, minimum width=10em,minimum height=2em,draw]
(lenpre) at([yshift=3em]encoder.north)
{
长度预测器
}
;
\node
[rounded corners=3pt,
thick,
fill=red!20, drop shadow, minimum width=10em,minimum height=4em,draw]
(encoder) at (0,0)
{
编码器
}
;
\node
[anchor=north,rounded corners=3pt,
thick,
fill=yellow!20, drop shadow, minimum width=10em,minimum height=2em,draw]
(lenpre) at([yshift=3em]encoder.north)
{
长度预测器
}
;
\node
[anchor=north]
(lable) at([xshift=3.5em,yshift=2.5em]lenpre.north)
{
译文长度:4
}
;
\node
[anchor=west, rounded corners=3pt, fill=blue!20, drop shadow, minimum width=16em,minimum height=4em,draw]
(decoder) at ([xshift=1.8cm]encoder.east)
{
解码器
}
;
\node
[anchor=west, rounded corners=3pt,
thick,
fill=blue!20, drop shadow, minimum width=16em,minimum height=4em,draw]
(decoder) at ([xshift=1.8cm]encoder.east)
{
解码器
}
;
\node
[anchor=north,emb]
(en2) at ([yshift=-1.3em]encoder.south)
{${
\mathbi
e
}
(
x
_
2
)
$}
;
\node
[anchor=north,emb]
(en1) at ([yshift=-1.3em,xshift=-3em]encoder.south)
{${
\mathbi
e
}
(
x
_
1
)
$}
;
...
...
@@ -61,7 +61,7 @@
\end{scope}
\begin{scope}
[yshift=2.8in]
\node
[rounded corners=3pt, fill=red!20, drop shadow, minimum width=10em,minimum height=4em,draw]
(encoder) at (0,0)
{
编码器
}
;
\node
[rounded corners=3pt,
thick,
fill=red!20, drop shadow, minimum width=10em,minimum height=4em,draw]
(encoder) at (0,0)
{
编码器
}
;
\node
[anchor=west,minimum width=16em,minimum height=4em]
(decoder) at ([xshift=1.8cm]encoder.east)
{}
;
\node
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...
...
@@ -122,7 +122,7 @@
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\end{scope}
...
...
Chapter15/Figures/figure-encoder-of-bidirectional-tree-structure.tex
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35e52982
...
...
@@ -2,10 +2,10 @@
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...
...
@@ -24,24 +24,24 @@
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...
...
Chapter15/Figures/figure-encoder-tree-structure-modeling.tex
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35e52982
...
...
@@ -2,7 +2,7 @@
\begin{tikzpicture}
\begin{scope}
\tikzstyle
{
hnode
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=[rectangle,inner sep=0mm,minimum height=2em,minimum width=4.5em,rounded corners=5pt,fill=
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...
...
@@ -10,12 +10,12 @@
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...
...
Chapter15/Figures/figure-layer-fusion-method.tex
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...
@@ -27,15 +27,15 @@
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[anchor=north,rectangle,minimum height=1.5em,minimum width=2.5em,rounded corners=5pt] (n10) at ([xshift=0em,yshift=-0.2em]n9.south)
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...
...
Chapter15/Figures/figure-main-flow-of-neural-network-structure-search.tex
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35e52982
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...
@@ -5,9 +5,9 @@
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[scale=0.36]
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every node
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...
...
Chapter15/Figures/figure-multi-task-structure.tex
查看文件 @
35e52982
...
...
@@ -2,7 +2,7 @@
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...
...
Chapter15/Figures/figure-structure-search-based-on-gradient-method.tex
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35e52982
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...
@@ -6,7 +6,7 @@
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...
...
Chapter15/Figures/figure-structure-search-based-on-reinforcement-learning.tex
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35e52982
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...
@@ -5,7 +5,7 @@
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...
...
Chapter15/Figures/figure-three-fusion-methods-of-tree-structure-information-1.tex
查看文件 @
35e52982
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...
@@ -4,7 +4,7 @@
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...
...
@@ -55,7 +55,7 @@
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...
...
Chapter15/Figures/figure-three-fusion-methods-of-tree-structure-information-2.tex
查看文件 @
35e52982
...
...
@@ -4,7 +4,7 @@
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...
...
@@ -48,9 +48,9 @@
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{$
\mathbi
{
h
}_{
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1
}$}
;
...
...
@@ -63,7 +63,7 @@
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{}
;
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Chapter15/chapter15.tex
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instead.
Chapter16/Figures/figure-shared-space-inductive-bilingual-dictionary.tex
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...
@@ -54,11 +54,11 @@
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[rec,anchor=center,rotate=60,fill=red!20]
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...
...
@@ -74,11 +74,11 @@
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...
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Chapter16/chapter16.tex
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差异被折叠。
点击展开。
Chapter17/Figures/figure-cache.tex
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...
...
@@ -17,10 +17,10 @@
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[anchor=south,font=\footnotesize,inner sep=0pt]
at ([yshift=0.2em]value.north)
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value
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缓存
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{${
\mathbi
{
d
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t
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[draw,anchor=east,
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minimum size=1.8em,fill=orange!15]
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{${
\mathbi
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d
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[anchor=north,font=\footnotesize]
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读取
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\mathbi
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[draw,anchor=east,minimum size=1.8em,fill=red!15]
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{$
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s
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t
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;
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[draw,anchor=east,
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minimum size=1.8em,fill=ugreen!15]
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s
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t
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;
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[draw,anchor=east,
thick,
minimum size=1.8em,fill=red!15]
(st2) at ([xshift=-0.85em,yshift=3.5em]dt.west)
{$
\widetilde
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[draw,thick,inner sep=0pt, minimum size=1.1em, circle]
(add) at ([yshift=-1.5em]st2.south)
{}
;
...
...
@@ -29,7 +29,7 @@
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[anchor=north,inner sep=0pt,font=\footnotesize,text=red]
at ([xshift=-0em,yshift=-0.5em]add.south)
{
融合
}
;
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[draw,anchor=east,minimum size=1.8em,fill=yellow!15]
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{
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C
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;
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{
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;
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[anchor=east]
(y) at ([xshift=-6em,yshift=1em]st.west)
{$
\mathbi
{
y
}_{
t
-
1
}$}
;
...
...
@@ -53,12 +53,12 @@
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(ct.0) to ([yshift=-2.5em]box.180);
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\draw
[-,
very
thick,out=0,in=-135]
(st.0) to (add.-135);
\draw
[-,
very
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(dt.180) to (add.-45);
\draw
[-latex,
very
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(add.90) -- (st2.-90);
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[-latex,
very
thick,out=100,in=-100]
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\end{tikzpicture}
\ No newline at end of file
Chapter17/chapter17.tex
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35e52982
...
...
@@ -160,11 +160,11 @@
%----------------------------------------------------------------------------------------------------
\begin{itemize}
\vspace
{
0.5em
}
\item
错误传播问题
。级联模型导致的一个很严重的问题在于,语音识别模型得到的文本如果存在错误,这些错误很可能在翻译过程中被放大,从而使最后翻译结果出现比较大的偏差。比如识别时在句尾少生成了个“吗”,会导致翻译模型将疑问句翻译为陈述句。
\item
{
\small\bfnew
{
错误传播问题
}}
。级联模型导致的一个很严重的问题在于,语音识别模型得到的文本如果存在错误,这些错误很可能在翻译过程中被放大,从而使最后翻译结果出现比较大的偏差。比如识别时在句尾少生成了个“吗”,会导致翻译模型将疑问句翻译为陈述句。
\vspace
{
0.5em
}
\item
翻译效率问题
。由于需要语音识别模型和文本标注模型只能串行地计算,翻译效率相对较低,而实际很多场景中都需要达到低延时的翻译。
\item
{
\small\bfnew
{
翻译效率问题
}}
。由于需要语音识别模型和文本标注模型只能串行地计算,翻译效率相对较低,而实际很多场景中都需要达到低延时的翻译。
\vspace
{
0.5em
}
\item
语音中的副语言信息丢失
。将语音识别为文本的过程中,语音中包含的语气、情感、音调等信息会丢失,而同一句话在不同的语气中表达的意思很可能是不同的。尤其是在实际应用中,由于语音识别结果通常并不包含标点,还需要额外的后处理模型将标点还原,也会带来额外的计算代价。
\item
{
\small\bfnew
{
语音中的副语言信息丢失
}}
。将语音识别为文本的过程中,语音中包含的语气、情感、音调等信息会丢失,而同一句话在不同的语气中表达的意思很可能是不同的。尤其是在实际应用中,由于语音识别结果通常并不包含标点,还需要额外的后处理模型将标点还原,也会带来额外的计算代价。
\vspace
{
0.5em
}
\end{itemize}
%----------------------------------------------------------------------------------------------------
...
...
@@ -199,9 +199,9 @@
%----------------------------------------------------------------------------------------------------
\begin{itemize}
\vspace
{
0.5em
}
\item
训练数据稀缺
。虽然语音识别和文本翻译的训练数据都很多,但是直接由源语言语音到目标语言文本的平行数据十分有限,因此端到端语音翻译天然地就是一种低资源翻译任务。
\item
{
\small\bfnew
{
训练数据稀缺
}}
。虽然语音识别和文本翻译的训练数据都很多,但是直接由源语言语音到目标语言文本的平行数据十分有限,因此端到端语音翻译天然地就是一种低资源翻译任务。
\vspace
{
0.5em
}
\item
建模复杂度更高
。在语音识别中,模型是学习如何生成语音对应的文字序列,输入和输出的对齐比较简单,不涉及到调序的问题。在文本翻译中,模型要学习如何生成源语言序列对应的目标语言序列,仅需要学习不同语言之间的映射,不涉及到模态的转换。而语音翻译模型需要学习从语音到目标语言文本的生成,任务更加复杂。
\item
{
\small\bfnew
{
建模复杂度更高
}}
。在语音识别中,模型是学习如何生成语音对应的文字序列,输入和输出的对齐比较简单,不涉及到调序的问题。在文本翻译中,模型要学习如何生成源语言序列对应的目标语言序列,仅需要学习不同语言之间的映射,不涉及到模态的转换。而语音翻译模型需要学习从语音到目标语言文本的生成,任务更加复杂。
\vspace
{
0.5em
}
\end{itemize}
%----------------------------------------------------------------------------------------------------
...
...
@@ -231,9 +231,9 @@
%----------------------------------------------------------------------------------------------------
\begin{itemize}
\vspace
{
0.5em
}
\item
输入和输出之间的对齐是单调的
。也就是后面的输入只会预测与前面的序列相同或后面的输出内容。比如对于图
\ref
{
fig:17-8
}
中的例子,如果输入的位置t已经预测了字符l,那么t之后的位置不会再预测前面的字符h和e。
\item
{
\small\bfnew
{
输入和输出之间的对齐是单调的
}}
。也就是后面的输入只会预测与前面的序列相同或后面的输出内容。比如对于图
\ref
{
fig:17-8
}
中的例子,如果输入的位置t已经预测了字符l,那么t之后的位置不会再预测前面的字符h和e。
\vspace
{
0.5em
}
\item
输入和输出之间是多对一的关系
。也就是多个输入会对应到同一个输出上。这对于语音序列来说是非常自然的一件事情,由于输入的每个位置只包含非常短的语音特征,因此多个输入才可以对应到一个输出字符。
\item
{
\small\bfnew
{
输入和输出之间是多对一的关系
}}
。也就是多个输入会对应到同一个输出上。这对于语音序列来说是非常自然的一件事情,由于输入的每个位置只包含非常短的语音特征,因此多个输入才可以对应到一个输出字符。
\vspace
{
0.5em
}
\end{itemize}
%----------------------------------------------------------------------------------------------------
...
...
Chapter8/chapter8.tex
查看文件 @
35e52982
...
...
@@ -532,9 +532,9 @@ span\textrm{[0,4]}&=&\textrm{“猫} \quad \textrm{喜欢} \quad \textrm{吃} \q
\begin{itemize}
\vspace
{
0.5em
}
\item
剪枝
:在CKY中,每个跨度都可以生成非常多的推导(局部翻译假设)。理论上,这些推导的数量会和跨度大小成指数关系。显然不可能保存如此大量的翻译推导。对于这个问题,常用的办法是只保留top-
$
k
$
个推导。也就是每个局部结果只保留最好的
$
k
$
个,即束剪枝。在极端情况下,当
$
k
$
=1时,这个方法就变成了贪婪的方法;
\item
{
\small\bfnew
{
剪枝
}}
:在CKY中,每个跨度都可以生成非常多的推导(局部翻译假设)。理论上,这些推导的数量会和跨度大小成指数关系。显然不可能保存如此大量的翻译推导。对于这个问题,常用的办法是只保留top-
$
k
$
个推导。也就是每个局部结果只保留最好的
$
k
$
个,即束剪枝。在极端情况下,当
$
k
$
=1时,这个方法就变成了贪婪的方法;
\vspace
{
0.5em
}
\item
$
n
$
-best结果的生成
:
$
n
$
-best推导(译文)的生成是统计机器翻译必要的功能。比如,最小错误率训练中就需要最好的
$
n
$
个结果用于特征权重调优。在基于CKY的方法中,整个句子的翻译结果会被保存在最大跨度所对应的结构中。因此一种简单的
$
n
$
-best生成方法是从这个结构中取出排名最靠前的
$
n
$
个结果。另外,也可以考虑自上而下遍历CKY生成的推导空间,得到更好的
$
n
$
-best结果
\upcite
{
huang2005better
}
。
\item
{
\small\bfnew
{$
n
$
-best结果的生成
}}
:
$
n
$
-best推导(译文)的生成是统计机器翻译必要的功能。比如,最小错误率训练中就需要最好的
$
n
$
个结果用于特征权重调优。在基于CKY的方法中,整个句子的翻译结果会被保存在最大跨度所对应的结构中。因此一种简单的
$
n
$
-best生成方法是从这个结构中取出排名最靠前的
$
n
$
个结果。另外,也可以考虑自上而下遍历CKY生成的推导空间,得到更好的
$
n
$
-best结果
\upcite
{
huang2005better
}
。
\end{itemize}
%----------------------------------------------------------------------------------------
% NEW SUB-SECTION
...
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ChapterAppend/chapterappend.tex
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