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NiuTrans
Toy-MT-Introduction
Commits
d1c4df30
Commit
d1c4df30
authored
Apr 12, 2020
by
xiaotong
Browse files
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Plain Diff
minor updates of section 2
parent
f1db191d
隐藏空白字符变更
内嵌
并排
正在显示
4 个修改的文件
包含
556 行增加
和
558 行删除
+556
-558
Book/Chapter2/chapter2.tex
+3
-5
Book/mt-book-xelatex.idx
+263
-263
Book/mt-book-xelatex.ptc
+284
-284
Book/mt-book-xelatex.tex
+6
-6
没有找到文件。
Book/Chapter2/chapter2.tex
查看文件 @
d1c4df30
...
@@ -783,7 +783,8 @@ N & = & \sum_{r=0}^{\infty}{r^{*}n_r} \nonumber \\
...
@@ -783,7 +783,8 @@ N & = & \sum_{r=0}^{\infty}{r^{*}n_r} \nonumber \\
也就是说,
$
N
$
仍然为这个整个样本分布最初的计数。样本中所有事件的概率之和为:
也就是说,
$
N
$
仍然为这个整个样本分布最初的计数。样本中所有事件的概率之和为:
\begin{eqnarray}
\begin{eqnarray}
\textrm
{
P
}
(r>0)
&
=
&
\sum
_{
r>0
}{
\textrm
{
P
}_
r
}
\nonumber
\\
\textrm
{
P
}
(r>0)
&
=
&
\sum
_{
r>0
}{
\textrm
{
P
}_
r
}
\nonumber
\\
&
=
&
1 -
\frac
{
n
_
1
}{
N
}
< 1
&
=
&
1 -
\frac
{
n
_
1
}{
N
}
\nonumber
\\
&
<
&
1
\label
{
eq:2.4-11
}
\label
{
eq:2.4-11
}
\end{eqnarray}
\end{eqnarray}
...
@@ -882,7 +883,7 @@ c_{\textrm{KN}}(\cdot) & = & \begin{cases} \textrm{count}(\cdot)\quad\quad \text
...
@@ -882,7 +883,7 @@ c_{\textrm{KN}}(\cdot) & = & \begin{cases} \textrm{count}(\cdot)\quad\quad \text
\end{eqnarray}
\end{eqnarray}
\noindent
其中catcount
$
(
\cdot
)
$
表示的是基于某个单个词作为第
$
n
$
个词的
$
n
$
-gram的种类数目。
\noindent
其中catcount
$
(
\cdot
)
$
表示的是基于某个单个词作为第
$
n
$
个词的
$
n
$
-gram的种类数目。
\parinterval
Kneser-Ney平滑是很多语言模型工具的基础
\cite
{
wang-etal-2018-niutrans
}
\cite
{
heafield-2011-kenlm
}
\cite
{
stolcke2002srilm
}
。还有很多
基于此为基础衍生出来的算法,有
兴趣的读者可以通过参考文献自行了解
\cite
{
parsing2009speech
}
\cite
{
ney1994structuring
}
\cite
{
chen1999empirical
}
。
\parinterval
Kneser-Ney平滑是很多语言模型工具的基础
\cite
{
wang-etal-2018-niutrans
}
\cite
{
heafield-2011-kenlm
}
\cite
{
stolcke2002srilm
}
。还有很多
以此为基础衍生出来的算法,感
兴趣的读者可以通过参考文献自行了解
\cite
{
parsing2009speech
}
\cite
{
ney1994structuring
}
\cite
{
chen1999empirical
}
。
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section
{
句法分析(短语结构分析)
}
\index
{
Chapter2.5
}
\section
{
句法分析(短语结构分析)
}
\index
{
Chapter2.5
}
...
@@ -948,7 +949,6 @@ c_{\textrm{KN}}(\cdot) & = & \begin{cases} \textrm{count}(\cdot)\quad\quad \text
...
@@ -948,7 +949,6 @@ c_{\textrm{KN}}(\cdot) & = & \begin{cases} \textrm{count}(\cdot)\quad\quad \text
一个上下文无关文法可以被视为一个系统
$
G
=
<N,
\Sigma
,R,S>
$
,其中
一个上下文无关文法可以被视为一个系统
$
G
=
<N,
\Sigma
,R,S>
$
,其中
\begin{itemize}
\begin{itemize}
\item
\item
$
N
$
为一个非终结符集合
\item
$
N
$
为一个非终结符集合
\item
$
\Sigma
$
为一个终结符集合
\item
$
\Sigma
$
为一个终结符集合
\item
$
R
$
为一个规则(产生式)集合,每条规则
$
r
\in
R
$
的形式为
$
X
\to
Y
_
1
Y
_
2
...Y
_
n
$
,其中
$
X
\in
N
$
,
$
Y
_
i
\in
N
\cup
\Sigma
$
\item
$
R
$
为一个规则(产生式)集合,每条规则
$
r
\in
R
$
的形式为
$
X
\to
Y
_
1
Y
_
2
...Y
_
n
$
,其中
$
X
\in
N
$
,
$
Y
_
i
\in
N
\cup
\Sigma
$
...
@@ -1016,7 +1016,6 @@ s_0 \overset{r_1}{\Rightarrow} s_1 \overset{r_2}{\Rightarrow} s_2 \overset{r_3}{
...
@@ -1016,7 +1016,6 @@ s_0 \overset{r_1}{\Rightarrow} s_1 \overset{r_2}{\Rightarrow} s_2 \overset{r_3}{
且
且
\begin{itemize}
\begin{itemize}
\item
\item
$
\forall
i
\in
[
0
,n
]
, s
_
i
\in
(
N
\cup\Sigma
)
^
*
$
\hspace
{
3.5em
}
$
\lhd
$
$
s
_
i
$
为合法的字符串
\item
$
\forall
i
\in
[
0
,n
]
, s
_
i
\in
(
N
\cup\Sigma
)
^
*
$
\hspace
{
3.5em
}
$
\lhd
$
$
s
_
i
$
为合法的字符串
\item
$
\forall
j
\in
[
1
,n
]
, r
_
j
\in
R
$
\hspace
{
6.3em
}
$
\lhd
$
$
r
_
j
$
为
$
G
$
的规则
\item
$
\forall
j
\in
[
1
,n
]
, r
_
j
\in
R
$
\hspace
{
6.3em
}
$
\lhd
$
$
r
_
j
$
为
$
G
$
的规则
\item
$
s
_
0
\in
S
$
\hspace
{
10.9em
}
$
\lhd
$
$
s
_
0
$
为起始非终结符
\item
$
s
_
0
\in
S
$
\hspace
{
10.9em
}
$
\lhd
$
$
s
_
0
$
为起始非终结符
...
@@ -1092,7 +1091,6 @@ s_0 \overset{r_1}{\Rightarrow} s_1 \overset{r_2}{\Rightarrow} s_2 \overset{r_3}{
...
@@ -1092,7 +1091,6 @@ s_0 \overset{r_1}{\Rightarrow} s_1 \overset{r_2}{\Rightarrow} s_2 \overset{r_3}{
一个概率上下文无关文法可以被视为一个系统
$
G
=
<N,
\Sigma
,R,S>
$
,其中
一个概率上下文无关文法可以被视为一个系统
$
G
=
<N,
\Sigma
,R,S>
$
,其中
\begin{itemize}
\begin{itemize}
\item
\item
$
N
$
为一个非终结符集合
\item
$
N
$
为一个非终结符集合
\item
$
\Sigma
$
为一个终结符集合
\item
$
\Sigma
$
为一个终结符集合
\item
$
R
$
为一个规则(产生式)集合,每条规则
$
r
\in
R
$
的形式为
$
p:X
\to
Y
_
1
Y
_
2
...Y
_
n
$
,其中
$
X
\in
N
$
,
$
Y
_
i
\in
N
\cup
\Sigma
$
,每个
$
r
$
都对应一个概率
$
p
$
,表示其生成的可能性。
\item
$
R
$
为一个规则(产生式)集合,每条规则
$
r
\in
R
$
的形式为
$
p:X
\to
Y
_
1
Y
_
2
...Y
_
n
$
,其中
$
X
\in
N
$
,
$
Y
_
i
\in
N
\cup
\Sigma
$
,每个
$
r
$
都对应一个概率
$
p
$
,表示其生成的可能性。
...
...
Book/mt-book-xelatex.idx
查看文件 @
d1c4df30
\indexentry{Chapter1.1|hyperpage}{
13
}
\indexentry{Chapter1.1|hyperpage}{
9
}
\indexentry{Chapter1.2|hyperpage}{1
6
}
\indexentry{Chapter1.2|hyperpage}{1
2
}
\indexentry{Chapter1.3|hyperpage}{
21
}
\indexentry{Chapter1.3|hyperpage}{
17
}
\indexentry{Chapter1.4|hyperpage}{
22
}
\indexentry{Chapter1.4|hyperpage}{
18
}
\indexentry{Chapter1.4.1|hyperpage}{
22
}
\indexentry{Chapter1.4.1|hyperpage}{
18
}
\indexentry{Chapter1.4.2|hyperpage}{2
4
}
\indexentry{Chapter1.4.2|hyperpage}{2
0
}
\indexentry{Chapter1.4.3|hyperpage}{2
5
}
\indexentry{Chapter1.4.3|hyperpage}{2
1
}
\indexentry{Chapter1.4.4|hyperpage}{2
6
}
\indexentry{Chapter1.4.4|hyperpage}{2
2
}
\indexentry{Chapter1.4.5|hyperpage}{2
7
}
\indexentry{Chapter1.4.5|hyperpage}{2
3
}
\indexentry{Chapter1.5|hyperpage}{2
8
}
\indexentry{Chapter1.5|hyperpage}{2
4
}
\indexentry{Chapter1.5.1|hyperpage}{2
8
}
\indexentry{Chapter1.5.1|hyperpage}{2
4
}
\indexentry{Chapter1.5.2|hyperpage}{2
9
}
\indexentry{Chapter1.5.2|hyperpage}{2
5
}
\indexentry{Chapter1.5.2.1|hyperpage}{2
9
}
\indexentry{Chapter1.5.2.1|hyperpage}{2
5
}
\indexentry{Chapter1.5.2.2|hyperpage}{
31
}
\indexentry{Chapter1.5.2.2|hyperpage}{
27
}
\indexentry{Chapter1.5.2.3|hyperpage}{
31
}
\indexentry{Chapter1.5.2.3|hyperpage}{
27
}
\indexentry{Chapter1.6|hyperpage}{
32
}
\indexentry{Chapter1.6|hyperpage}{
28
}
\indexentry{Chapter1.7|hyperpage}{3
4
}
\indexentry{Chapter1.7|hyperpage}{3
0
}
\indexentry{Chapter1.7.1|hyperpage}{3
4
}
\indexentry{Chapter1.7.1|hyperpage}{3
0
}
\indexentry{Chapter1.7.1.1|hyperpage}{3
5
}
\indexentry{Chapter1.7.1.1|hyperpage}{3
1
}
\indexentry{Chapter1.7.1.2|hyperpage}{3
6
}
\indexentry{Chapter1.7.1.2|hyperpage}{3
2
}
\indexentry{Chapter1.7.2|hyperpage}{3
8
}
\indexentry{Chapter1.7.2|hyperpage}{3
4
}
\indexentry{Chapter1.8|hyperpage}{
40
}
\indexentry{Chapter1.8|hyperpage}{
36
}
\indexentry{Chapter2.1|hyperpage}{4
6
}
\indexentry{Chapter2.1|hyperpage}{4
2
}
\indexentry{Chapter2.2|hyperpage}{4
7
}
\indexentry{Chapter2.2|hyperpage}{4
3
}
\indexentry{Chapter2.2.1|hyperpage}{4
7
}
\indexentry{Chapter2.2.1|hyperpage}{4
3
}
\indexentry{Chapter2.2.2|hyperpage}{4
9
}
\indexentry{Chapter2.2.2|hyperpage}{4
5
}
\indexentry{Chapter2.2.3|hyperpage}{
50
}
\indexentry{Chapter2.2.3|hyperpage}{
46
}
\indexentry{Chapter2.2.4|hyperpage}{
51
}
\indexentry{Chapter2.2.4|hyperpage}{
47
}
\indexentry{Chapter2.2.5|hyperpage}{
53
}
\indexentry{Chapter2.2.5|hyperpage}{
49
}
\indexentry{Chapter2.2.5.1|hyperpage}{
53
}
\indexentry{Chapter2.2.5.1|hyperpage}{
49
}
\indexentry{Chapter2.2.5.2|hyperpage}{5
4
}
\indexentry{Chapter2.2.5.2|hyperpage}{5
0
}
\indexentry{Chapter2.2.5.3|hyperpage}{5
4
}
\indexentry{Chapter2.2.5.3|hyperpage}{5
0
}
\indexentry{Chapter2.3|hyperpage}{5
5
}
\indexentry{Chapter2.3|hyperpage}{5
1
}
\indexentry{Chapter2.3.1|hyperpage}{5
6
}
\indexentry{Chapter2.3.1|hyperpage}{5
2
}
\indexentry{Chapter2.3.2|hyperpage}{5
7
}
\indexentry{Chapter2.3.2|hyperpage}{5
3
}
\indexentry{Chapter2.3.2.1|hyperpage}{5
7
}
\indexentry{Chapter2.3.2.1|hyperpage}{5
3
}
\indexentry{Chapter2.3.2.2|hyperpage}{5
8
}
\indexentry{Chapter2.3.2.2|hyperpage}{5
4
}
\indexentry{Chapter2.3.2.3|hyperpage}{
60
}
\indexentry{Chapter2.3.2.3|hyperpage}{
56
}
\indexentry{Chapter2.4|hyperpage}{
62
}
\indexentry{Chapter2.4|hyperpage}{
58
}
\indexentry{Chapter2.4.1|hyperpage}{
63
}
\indexentry{Chapter2.4.1|hyperpage}{
59
}
\indexentry{Chapter2.4.2|hyperpage}{6
5
}
\indexentry{Chapter2.4.2|hyperpage}{6
1
}
\indexentry{Chapter2.4.2.1|hyperpage}{6
6
}
\indexentry{Chapter2.4.2.1|hyperpage}{6
2
}
\indexentry{Chapter2.4.2.2|hyperpage}{6
7
}
\indexentry{Chapter2.4.2.2|hyperpage}{6
3
}
\indexentry{Chapter2.4.2.3|hyperpage}{6
8
}
\indexentry{Chapter2.4.2.3|hyperpage}{6
4
}
\indexentry{Chapter2.5|hyperpage}{
70
}
\indexentry{Chapter2.5|hyperpage}{
66
}
\indexentry{Chapter2.5.1|hyperpage}{
70
}
\indexentry{Chapter2.5.1|hyperpage}{
66
}
\indexentry{Chapter2.5.2|hyperpage}{
72
}
\indexentry{Chapter2.5.2|hyperpage}{
68
}
\indexentry{Chapter2.5.3|hyperpage}{7
6
}
\indexentry{Chapter2.5.3|hyperpage}{7
2
}
\indexentry{Chapter2.6|hyperpage}{7
8
}
\indexentry{Chapter2.6|hyperpage}{7
4
}
\indexentry{Chapter3.1|hyperpage}{
83
}
\indexentry{Chapter3.1|hyperpage}{
79
}
\indexentry{Chapter3.2|hyperpage}{8
5
}
\indexentry{Chapter3.2|hyperpage}{8
1
}
\indexentry{Chapter3.2.1|hyperpage}{8
5
}
\indexentry{Chapter3.2.1|hyperpage}{8
1
}
\indexentry{Chapter3.2.1.1|hyperpage}{8
5
}
\indexentry{Chapter3.2.1.1|hyperpage}{8
1
}
\indexentry{Chapter3.2.1.2|hyperpage}{8
6
}
\indexentry{Chapter3.2.1.2|hyperpage}{8
2
}
\indexentry{Chapter3.2.1.3|hyperpage}{8
7
}
\indexentry{Chapter3.2.1.3|hyperpage}{8
3
}
\indexentry{Chapter3.2.2|hyperpage}{8
7
}
\indexentry{Chapter3.2.2|hyperpage}{8
3
}
\indexentry{Chapter3.2.3|hyperpage}{8
8
}
\indexentry{Chapter3.2.3|hyperpage}{8
4
}
\indexentry{Chapter3.2.3.1|hyperpage}{8
8
}
\indexentry{Chapter3.2.3.1|hyperpage}{8
4
}
\indexentry{Chapter3.2.3.2|hyperpage}{8
9
}
\indexentry{Chapter3.2.3.2|hyperpage}{8
5
}
\indexentry{Chapter3.2.3.3|hyperpage}{
90
}
\indexentry{Chapter3.2.3.3|hyperpage}{
86
}
\indexentry{Chapter3.2.4|hyperpage}{
91
}
\indexentry{Chapter3.2.4|hyperpage}{
87
}
\indexentry{Chapter3.2.4.1|hyperpage}{
91
}
\indexentry{Chapter3.2.4.1|hyperpage}{
87
}
\indexentry{Chapter3.2.4.2|hyperpage}{
93
}
\indexentry{Chapter3.2.4.2|hyperpage}{
89
}
\indexentry{Chapter3.2.5|hyperpage}{9
4
}
\indexentry{Chapter3.2.5|hyperpage}{9
0
}
\indexentry{Chapter3.3|hyperpage}{9
7
}
\indexentry{Chapter3.3|hyperpage}{9
3
}
\indexentry{Chapter3.3.1|hyperpage}{9
7
}
\indexentry{Chapter3.3.1|hyperpage}{9
3
}
\indexentry{Chapter3.3.2|hyperpage}{
100
}
\indexentry{Chapter3.3.2|hyperpage}{
96
}
\indexentry{Chapter3.3.2.1|hyperpage}{
101
}
\indexentry{Chapter3.3.2.1|hyperpage}{
97
}
\indexentry{Chapter3.3.2.2|hyperpage}{
102
}
\indexentry{Chapter3.3.2.2|hyperpage}{
98
}
\indexentry{Chapter3.3.2.3|hyperpage}{
103
}
\indexentry{Chapter3.3.2.3|hyperpage}{
99
}
\indexentry{Chapter3.4|hyperpage}{10
4
}
\indexentry{Chapter3.4|hyperpage}{10
0
}
\indexentry{Chapter3.4.1|hyperpage}{10
4
}
\indexentry{Chapter3.4.1|hyperpage}{10
0
}
\indexentry{Chapter3.4.2|hyperpage}{10
6
}
\indexentry{Chapter3.4.2|hyperpage}{10
2
}
\indexentry{Chapter3.4.3|hyperpage}{10
7
}
\indexentry{Chapter3.4.3|hyperpage}{10
3
}
\indexentry{Chapter3.4.4|hyperpage}{10
8
}
\indexentry{Chapter3.4.4|hyperpage}{10
4
}
\indexentry{Chapter3.4.4.1|hyperpage}{10
8
}
\indexentry{Chapter3.4.4.1|hyperpage}{10
4
}
\indexentry{Chapter3.4.4.2|hyperpage}{10
9
}
\indexentry{Chapter3.4.4.2|hyperpage}{10
5
}
\indexentry{Chapter3.5|hyperpage}{11
4
}
\indexentry{Chapter3.5|hyperpage}{11
0
}
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5
}
\indexentry{Chapter3.5.1|hyperpage}{11
1
}
\indexentry{Chapter3.5.2|hyperpage}{11
7
}
\indexentry{Chapter3.5.2|hyperpage}{11
3
}
\indexentry{Chapter3.5.3|hyperpage}{11
9
}
\indexentry{Chapter3.5.3|hyperpage}{11
5
}
\indexentry{Chapter3.5.4|hyperpage}{1
20
}
\indexentry{Chapter3.5.4|hyperpage}{1
16
}
\indexentry{Chapter3.5.5|hyperpage}{1
22
}
\indexentry{Chapter3.5.5|hyperpage}{1
18
}
\indexentry{Chapter3.5.5|hyperpage}{12
4
}
\indexentry{Chapter3.5.5|hyperpage}{12
0
}
\indexentry{Chapter3.6|hyperpage}{12
5
}
\indexentry{Chapter3.6|hyperpage}{12
1
}
\indexentry{Chapter3.6.1|hyperpage}{12
5
}
\indexentry{Chapter3.6.1|hyperpage}{12
1
}
\indexentry{Chapter3.6.2|hyperpage}{12
6
}
\indexentry{Chapter3.6.2|hyperpage}{12
2
}
\indexentry{Chapter3.6.4|hyperpage}{12
7
}
\indexentry{Chapter3.6.4|hyperpage}{12
3
}
\indexentry{Chapter3.6.5|hyperpage}{12
7
}
\indexentry{Chapter3.6.5|hyperpage}{12
3
}
\indexentry{Chapter3.7|hyperpage}{12
7
}
\indexentry{Chapter3.7|hyperpage}{12
3
}
\indexentry{Chapter4.1|hyperpage}{12
9
}
\indexentry{Chapter4.1|hyperpage}{12
5
}
\indexentry{Chapter4.1.1|hyperpage}{1
31
}
\indexentry{Chapter4.1.1|hyperpage}{1
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\contentsline {subsubsection}{(一)早期的人工神经网络和第一次寒冬}{20
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\contentsline {subsubsection}{(二)深度学习的效果}{2
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\contentsline {subsubsection}{标量、向量和矩阵}{2
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\contentsline {subsubsection}{标量、向量和矩阵}{2
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\contentsline {subsubsection}{矩阵的转置}{2
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08
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08
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\contentsline {subsubsection}{线性映射}{21
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\contentsline {subsubsection}{(一)感知机\ \raisebox {0.5mm}{------}\ 最简单的人工神经元模型}{21
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\contentsline {subsubsection}{(二)神经元内部权重}{21
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\contentsline {subsubsection}{(三)神经元的输入\ \raisebox {0.5mm}{------}\ 离散 vs 连续}{21
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\contentsline {subsubsection}{(四)神经元内部的参数学习}{21
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\contentsline {subsubsection}{线性变换和激活函数}{2
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\contentsline {subsubsection}{张量的矩阵乘法}{2
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\contentsline {subsubsection}{(一)梯度下降}{2
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% CHAPTERS
% CHAPTERS
%----------------------------------------------------------------------------------------
%----------------------------------------------------------------------------------------
%
\include{Chapter1/chapter1}
\include
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Chapter1/chapter1
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\include
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Chapter2/chapter2
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\include{Chapter3/chapter3}
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\include{Chapter4/chapter4}
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Chapter4/chapter4
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Chapter5/chapter5
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\include{Chapter6/chapter6}
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