Automatic Comma Insertion for Japanese Text Generation
Masaki Murata
Graduate School ofInformation Science,
Nagoya University, Japan

Tomohiro Ohno
Graduate School ofInternational Development,
Nagoya University, Japan

Shigeki Matsubara
Graduate School ofInformation Science,
Nagoya University, Japan

murata@el.itc.nagoya-u.ac.jp

ohno@nagoya-u.jp

matubara@nagoya-u.jp

Abstract
This paper proposes a method for automatically inserting commas into Japanese texts.
In Japanese sentences, commas play an important role in explicitly separating the constituents, such as words and phrases, of a sentence. The method can be used as an elemental technology for natural language generation such as speech recognition and machine translation, or in writing-support tools
for non-native speakers. We categorized theusages of commas and investigated the appearance tendency of each category. In thismethod, the positions where commas should
be inserted are decided based on a machinelearning approach. We conducted a comma
insertion experiment using a text corpus andconfirmed the effectiveness of our method.

1 Introduction
In Japanese sentences, commas are inserted to markword boundaries that might be otherwise unclear because Japanese is a non-segmented language. They
are also inserted at sharp semantic boundaries to improve the readability of a sentence. While there is atendency about the positions where commas should
be inserted in a Japanese sentence, there is no clear
standard for these positions. Therefore, it is hardfor non-natives of Japanese such as foreign students
to insert commas properly, and the method for automatic comma insertion is required to support sentence generation by such people. In addition, thismethod is expected to be useful for improving readability of texts generated by automatic speech recognition or machine translation.
This paper proposes a method for automaticallyinserting commas into Japanese texts. There areseveral usages of commas, and the positions to insert commas depend on these usages. Therefore,
we grouped the usages of commas into nine categories, and investigated the appearance tendency foreach category to find the effective features of machine learning by using Japanese newspaper articles. Based on the analysis of comma positions, ourmethod decides whether or not to insert a comma
at each bunsetsu1 boundary in an input sentence bymachine learning.
We conducted an experiment on comma insertion
using the Kyoto Text Corpus (Kurohashi and Nagao,
1998), and obtained higher recall and precision thanthose of the baseline, leading us to confirm the effectiveness of our method.
This paper is organized as follows: The next section presents related works. Section 3 gives preliminary analyses. Section 4 explains how our comma
insertion method works. An experiment and discussions are presented in Sections 5 and 6, respectively.

2 Related Works
There have been many investigations on comma insertion into output texts of speech recognition systems to improve the readability (Christensen et al.,
2001; Kim and Woodland, 2001; Liu et al., 2006;
Shimizu et al., 2008). Their methods insert commas
using pause information of speakers, based on theidea that a point at which a speaker takes a breath
partly corresponds to a point where a comma is inserted. However, since pause information cannot be
obtained from texts, we cannot use this approach because our targets are written texts.
In addition, there have been some investigations
1

Bunsetsu is a linguistic unit in Japanese that roughly corresponds to a basic phrase in English. A bunsetsu consists of one
independent word and zero or more ancillary words.

on comma insertion into non-Japanese written texts(White and Rajkumar, 2008; Guo et al., 2010). In
Japanese, there are several usages of commas, andsome usages are specific to Japanese due to its linguistic nature. Therefore, just adopting the above
mentioned methods, which have been developed
to process non-Japanese texts, is not sufficient toenable high-quality comma insertion into Japanese
sentences. Development of a method based on thedetailed analysis of Japanese commas is required.
Furthermore, there have been some investigations on comma insertion into Japanese written texts(Hayashi, 1992; Suzuki et al., 1995). These investigations have adopted rule-based methods. However,the number of their rules is not necessarily sufficient,and no quantitative evaluation has been performed.

3

Table 1: Categorization of usages of commas# usage of comma
1 commas between clauses
2 commas indicating clear dependency relations
3 commas for avoiding reading mistakes andreading difficulty
4 commas indicating the subject
5 commas inserted after a conjunction or
adverb at the beginning of a sentence
6 commas inserted between parallel words orphrases
7 commas inserted after an adverbial phrase toindicate time
8 commas emphasizing the adjacent word
9 other

Analyses on Comma Usages

There have been several discussions on commas,
including the draft of “Kutou-hou (punctuation)”made by Archives Division, Minister’s Secretariat,
Japanese Ministry of Education, Science and Culture in 1906. There are several usages of commas,
and depending on the usage, the types of positions
where commas are inserted are different. First, we
examined some previous publications on commas(Honda, 1982; Inukai, 2002; Shogakukan’s editiorial department, 2007). Based on the results of the examination, we classified the usages of commas intonine categories shown in Table 1. Here, commas
in Japanese sentences and commas in English sentences have some common roles. In Japanese sentences, some commas have the same roles as commas in English sentences, but some commas haveroles specific to Japanese due to its linguistic naturesuch as “Japanese is a non-segmented language” or“Japanese has kanji characters and katakana characters.”
In our study, positions where a comma should
be inserted are detected by using machine learning.
We investigated the Kyoto Text Corpus version 4.0(Kurohashi and Nagao, 1998) to find the effective
features. The Kyoto Text Corpus is a collection ofJapanese articles of Mainichi newspaper. We used
the articles on January 1st and from January 3rd to
11th in 1995 as the analysis data. Table 2 shows
the size of the data. The data had been manually

Table 2: Size of the analysis data

sentencesbunsetsus
characterscommascharacters per sentence

11,821
117,501
503,970
16,59542.63

annotated with information on morphological analysis, bunsetsu segmentation and dependency2 analysis. Clause boundaries were detected by the clauseboundary detection program CBAP (Kashioka andMaruyama, 2004).
Out of all the inserted commas, only 1.43%
were inserted at positions which were not bunsetsuboundaries. Therefore, we analyzed only commas
inserted at bunsetsu boundaries. Of 105,680 bunsetsu boundaries, commas were inserted at 16,357
bunsetsu boundaries, that is, the rate of comma
insertion was 15.48%. In the following sections,
we focus on morphemes, clause boundaries, dependency relation and the number of characters between
commas, and investigate their relations with commas.
3.1 Commas between Clauses
If a sentence consists of several clauses, insertinga comma between clauses makes clear the sentence2

A dependency in a Japanese sentence is a modification relation in which a modifier bunsetsu depends on a modified bunsetsu. That is, the modifier bunsetsu and the modified bunsetsu
work as a modifier and a modifyee, respectively.

Table 3: Rates of comma insertion according to the clauseboundary type

type of clause boundary
topicalized element-wa
adnominal clausecontinuous clausecompound clause-te
quotational clause
supplement clausediscourse marker
compound clause-ga
compound clause-decondition clause-to

ratio of comma
insertion (%)
16.94 (1,446/8,536)
0.72(43/5,960)
84.57 (2,685/3,175)
23.31(394/1,690)
4.40(74/1,680)
17.53(245/1,398)60.13(650/1,081)
93.85(946/1,008)
84.52(606/717)81.66(423/518)

structure. Therefore, a clause boundary is considered to be a strong candidate of a position where acomma is inserted. For example, in the following
sentence3 :• 国連による対イラク制裁解除に向け、関係の深い
仏に一層の協力を求めるのが狙いとみられる。
(Toward lifting the sanctions imposed on Iraq by
United Nations, the aim seems to be to request further cooperation from France, which has close ties
to Iraq.)

a comma is inserted at the clause boundary right after the continuous clause “国連による対イラク制
裁解除に向け (Toward lifting the sanctions imposedon Iraq by United Nations).” Like this example, thesame usage of commas is seen in English as well.
In the analysis data, there existed 29,278 clauseboundaries excluding sentence breaks. Amongthem, commas were inserted at 8,805 positions(30.01%). The rate is higher than that of bunsetsuboundaries. This indicates that commas tend to beinserted at clause boundaries.
We investigated the rate of comma insertion about
114 types4 of clause boundaries. Table 3 shows the
top 10 clause boundary types according to the occurrence frequency, and the rates of comma inser3
We underlined commas which we mentioned in the example and the corresponding positions in the translation of the example.
4
In our research, we used the types of clause boundaries defined by the Clause Boundary Annotation Program (Kashioka
and Maruyama, 2004).

世界
の

成長セ
ンター
と

なっ
た

アジア
で

of the a center becomes in
Asiaworld of thegrowth：bunsetsu

急浮上
する

中国
の

存在
は

希望
に

あふれて
いると同
時に

困難
な

課題
も

山積し
ている

strong ofpresence hope not only difficult problems causes
Chinabrings：dependency relation

世界の成長センターとなったアジアで、急浮上する中国の存在は、希望にあふれていると同時に、困難な課題も山積している。
(In Asia, which becomes a center of the growth of the world, the strong presence of China not
only brings hope but also causes difficult problems.)

Figure 1: Commas making clear dependency relations

tion. In cases of “continuous clause” and “compound clause-de,” the rates were higher than 84%.
On the other hand, in cases of “adnominal clause”
and “quotational clause,” the rates were lower than
5%. This means that the likelihoods of comma insertion are different according to the clause boundary
type.

3.2 Commas and Dependency Structure
Commas have a role to make dependency relations
clearer. Commas tend to be inserted right after abunsetsu that depends on a distant bunsetsu. In Figure 1, although the bunsetsu “アジアで (in Asia)”
depends on the bunsetsu “山積している (causes),”
if the comma right after the bunsetsu “アジアで (inAsia)” is not inserted, the readers might mistakenly
understand that the bunsetsu “アジアで (in Asia)”
depends on the next bunsetsu “急浮上する (strong).”
To avoid the mistake, the comma is inserted.
In the analysis data, there existed 66,984 bunsetsus which depend on the next bunsetsu. Among thebunsetsu boundaries right after them, 2,302 (3.44%)
were the positions where a comma was inserted. On
the other hand, in the case of a bunsetsu boundary right after a bunsetsu which does not depend on
the next bunsetsu, the rate of comma insertion was
36.32% (14,055/38,696).
In addition, when the modifyee of a bunsetsu islocated outside the clause containing the bunsetsu,
i.e. to the right of the clause end, commas are considered to be more frequently inserted right after thebunsetsu because such bunsetsu causes more complex dependency structure. The rate of comma insertion right after such bunsetsu is 54.24%.

3.3 Commas for Avoiding Reading Mistakes
and Reading Difficulty
Although, unlike English, Japanese is a nonsegmented language, word boundaries are easy todetect because Japanese has three types of characters; hiragana characters, katakana characters, andkanji characters. However, if the same types of characters appear sequentially, readers may make a reading mistake or feel difficulty in reading them. To
avoid such mistakes and difficulty, there is a usageof commas specific to Japanese.
In the following example, a comma is inserted
between two sequentially appearing words “焼却(burned)” and “灰 (ashes)” both of which consist of
only kanji characters.
• 川崎さんの遺体を群馬県利根郡片品村花咲の知人宅に運んで焼却、灰を同村の山林に捨てたことを認める内容という。(He seemed to acknowledge
that he had carried the corpse of Mr. Kawasaki to an
acquaintance in Hanasaki, Katashina-mura, Tonegun, Gunma Prefecture, burned it and abandoned
its ashes in the mountain forest in Katashina-mura.)

The comma was inserted because if there was nocomma, the word boundary would become unclear
and reading difficulty would be caused. Among
2,409 bunsetsu boundaries over which kanji characters appeared sequentially, commas were inserted at
2,188 (90.83%) bunsetsu boundaries. In the case of
katakana characters, the rate was 97.69% (211/216).
Commas tend to be inserted at most bunsetsu boundaries if kanji characters or katakana characters sequentially appear over a boundary.
3.4 Commas Indicating the Subject
Commas are considered to be inserted right after abunsetsu that represents the subject of a sentence.
For example, in Figure 2, a comma is inserted rightafter the bunsetsu “戦火は (war)” to indicate that thebunsetsu is the subject of the sentence. Here, we pay
attention to the clause boundary of the type “topicalized element-wa.” The rate that commas were inserted at the clause boundaries “topicalized elementwa” was 16.94% (1,446/8,536). This rate is almost
the same as that of bunsetsu boundaries. On theother hand, the commas inserted at the clause boundaries “topicalized element-wa” accounted for 8.84%(1,446/16,357) of all the inserted commas.

カンボジ
アでの

長い

long
in
Cambodia

戦火
は

メコン
を

開発
から

遠ざけ

川を

汚染など
から

隔離し
てきた

war Mekong from ahas kept the river fromhasdevelopment away
pollution etc. isolated：bunsetsu：dependency relation

カンボジアでの長い戦火は、メコンを開発から遠ざけ、川を汚染などから隔離してきた。
(A long war in Cambodia has kept away Mekong from a development, and has isolated
the river from pollution etc.)

Figure 2: Comma insertion at the clause boundary “topicalized element-wa”

In the case of the clause boundary “topicalized
element-wa” right after a bunsetsu which does notdepend on the next bunsetsu (e.g., the bunsetsu “戦
火は (war)” in Figure 2), the rate of comma insertion was 20.71% (1,426/6,886). The rate is higher
than that of all the clause boundaries “topicalized
element-wa.” This shows that commas tend to be
especially inserted at the “topicalized element-wa”
right after bunsetsus which do not depend on thenext bunsetsu.
3.5 Commas after Conjunction or Adverb
Commas tend to be inserted right after a conjunction or an adverb located at the beginning of a sentence. These commas correspond to English commas which are inserted right after a word such as“however” and “furthermore” located at the beginning of a sentence.
• しかし、私はそれに同感する気持ちになれない。
(However, I do not feel like agreeing on it.)In the analysis data, there existed 695 bunsetsus whose rightmost morpheme is a conjunction
and which are located at the beginning of a sentence. Among them, commas were inserted rightafter 498 (71.65%) bunsetsus. In the case of bunsetsus whose rightmost morpheme is an adverb, therate was 30.97% (140/452).
3.6 Commas Inserted between Parallel Words
or Phrases
Commas have a function which makes clear separation between parallel words or phrases. The following example shows commas separating parallel
nouns.

In this example, commas are inserted to separate
parallel nouns “環境 (environment),” “人口 (population)” and “食糧 (food)”. In English, there are commas which perform the same role. In fact, commas
were inserted between “environment” and “population” and between “population” and “food” in thetranslation of the above example. When bunsetsus
whose rightmost morpheme is a noun appear sequentially, the rate of comma insertion between suchbunsetsus is 59.39% (3,330/5,607).
Also, commas are inserted to separate parallelphrases. In the following example,• メニューは前夜、首相が何を食べたかを調べて同じ献立を避けたり、和食と洋食のバランスを考えたりして決める。(The menu is decided by avoiding the menu the Prime Minister ate on the previous
night, and by considering the balance between theJapanese food and the European food.)

a comma is inserted right after the bunsetsu “避けたり (avoiding)” to make clear separation between theparallel phrases “同じ献立を避けたり (by avoiding the menu)” and “和食と洋食のバランスを考えたりして (by considering the balance between theJapanese food and the European food).” The rateof comma insertion between two parallel phrases is
79.89% (751/940). This is much higher than that ofbunsetsu boundaries, indicating that commas tend to
be inserted when phrases are paralleled.
3.7 Number of Characters between Commas
If there are too many commas at a short distance,
the sentence becomes hard to read. Therefore, thenumber of characters between commas is expected
to be not too small. Also, because a long sequenceof characters without a comma is generated if the
distance between commas is very long, the occurrence frequency of such sequences of characters is
considered to be low.
We investigated the number of characters between
commas and its occurrence frequency. Figure 3

800
700

occurence frequency• むしろ地球規模の環境、人口、食糧など広範に国連の果たさなければならない役割は大きい。 (The
United Nations should play a lot of roles in a broad
range of fields, such as the global environment,
population, and food.)

600
500
400
300
200
100
0
1

3

5

7

9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43

number of characters

Figure 3: Number of characters between commas and its
occurrence frequency

shows the results of investigation. When the number of characters between commas is either large orsmall, the occurrence frequency is low.

4 Comma Insertion Method
In our method, a sentence, on which morphological analysis, bunsetsu segmentation, clause boundary analysis and dependency analysis have been performed, is considered the input. Our method decides whether or not to insert a comma at each bunsetsu boundary in an input sentence. Based on theanalysis results in Section 3, our method adopts thebunsetsu boundaries as candidate positions where acomma is inserted. Our method identifies the mostappropriate combination among all combinations ofpositions where a comma can be inserted, by using
the probabilistic model. In this paper, input sentences which consist of n bunsetsus are represented
by B = b1 · · · bn , and the results of comma insertion by R = r1 · · · rn . Here, ri is 1 if a comma
is inserted right after bunsetsu bi , and 0 otherwise.
We indicate the j-th sequence of bunsetsus createdby dividing an input sentence into m sequences as
Lj = bj1 · · · bjnj (1 ≤ j ≤ m), and then, rkj = 0 if
1 ≤ k < nj , and rkj = 1 if k = nj .
4.1 Probabilistic Model for Comma Insertion
When an input sentence B is provided, our method
identifies the comma insertion R that maximizes
the conditional probability P (R|B). Assuming thatwhether or not to insert a comma right after a bunsetsu is independent of other commas except theTable 4: Features used for the maximum entropy method
the rightmost independent morpheme, i.e. head word, (part-of-speech and inflected form) andrightmost morpheme (part-of-speech) of a bunsetsu bjk
the rightmost morpheme (a surface form) of bjk if the rightmost morpheme is a particle
the first morpheme (part-of-speech) of bjk+1
commas inserted
whether or not a clause boundary exists right after bjk
between clauses
type of a clause boundary right after bjk if there exists a clause boundarycommas indicating whether or not bjk depends on the next bunsetsu
clear dependency
whether or not bjk depends on a bunsetsu located after the final bunsetsu of the clause including
relationsthe next bunsetsu of bjk
whether or not bjk is depended on by the bunsetsu located right before it
whether or not the dependency structure of a sequence of bunsetsus between bjk and bj1 is closed
commas avoiding
whether or not both the rightmost morpheme of bjk and first morpheme of bjk+1 are kanji
reading mistakes and charactersreading difficulty
whether or not both the rightmost morpheme of bjk and first morpheme of bjk+1 are katakana
characterscommas indicating whether or not there exists a clause boundary “topicalized element-wa” right after bjk and bjk
the subject
depends on the next bunsetsu
whether or not there exists a clause boundary “topicalized element-wa” right after bjk and thestring of characters right before bjk is “では (dewa)”
the number of characters in a phrase indicating the subject5 if there exists a clause boundary“topicalized element-wa” right after bjk
whether or not a clause boundary “topicalized element-wa” exists right after bjk and a bunsetsu
whose rightmost morpheme is a verb depends on the modified bunsetsu of bjk
commas inserted
whether or not bjk appears at the beginning of a sentence and its rightmost morpheme is aafter a conjunction conjunction
or adverb at the be- whether or not bjk appears at the beginning of a sentence and its rightmost morpheme is an
ginning of a sentence adverb
commas inserted
whether or not both the rightmost morphemes of bjk and bjk+1 are nouns
between parallel
whether or not a predicate at the sentence end is depended on by bjk whose rightmost
independent morpheme is a verb and by any of the bunsetsus which are located after bjk and ofwords or phrases
which the rightmost independent morpheme is a verb
number of characters one of the following 4 categories if the number of characters from bj1 to bjk is found there
from bj1 to bjk([num = 1], [2 ≤ num ≤ 3], [4 ≤ num ≤ 21], [22 ≤ num])morphologicalinformation

one appearing immediately before that bunsetsu,
P (R|B) can be calculated as follows:
P (R|B)=P (r11 = 0, · · · , rn1 1 −1 = 0, rn1 1 = 1, · · · ,(1)

r1m = 0, · · · , rnmm −1 = 0, rnmm = 1|B)∼
=P (r11 = 0|B) × · · ·×P (rn1 1 −1 = 0|rn1 1 −2 = 0, · · · , r11 = 0, B)
×P (rn1 1 = 1|rn1 1 −1 = 0, · · · , r11 = 0, B) × · · ·×P (r1m = 0|rnm−1= 1, B) × · · ·m−1
×P (rnmm −1 = 0|rnmm −2 = 0,· · ·, r1m = 0, rnm−1= 1, B)
m−1
×P (rnmm = 1|rnmm −1 = 0, · · · , r1m = 0, rnm−1= 1, B)m−1

jwhere P (rkj = 1|rk−1= 0, · · · , r1j = 0, rnj−1=
j−1
1, B) is the probability that a comma is inserted rightafter a bunsetsu bjk when the sequence of bunsetsus B is provided and the position of j-th comma isjidentified. Similarly, P (rkj = 0|rk−1= 0, · · · , r1j =0, rnj−1= 1, B) is the probability that a commaj−1

is not inserted right after a bunsetsu bjk . These
probabilities are estimated by the maximum entropy
method. The result R which maximizes the conditional probability P (R|B) is regarded as the mostappropriate result of comma insertion, and calculated by dynamic programming.

4.2 Features on Maximum Entropy Method

Table 5: Size of test datajTo estimate P (rkj = 1|rk−1= 0, · · · , r1j =j0, rnj−1= 1, B) and P (rkj = 0|rk−1= 0, · · · , r1j =j−1
0, rnj−1= 1, B) by the maximum entropy method,j−1
we used the features in Table 4 based on the analysis
described in Section 3.

sentencesbunsetsus
characterscommascharacters per sentence

4,659
46,511
198,899
6,549
42.69

5 Experiment
To evaluate the effectiveness of our method, we conducted an experiment using a Japanese text corpus.
5.1 Outline of Experiment
As the experimental data, we used the newspaper articles in the Kyoto Text Corpus version 4.0 (Kurohashi and Nagao, 1998). We used the articles fromJanuary 14th to 17th as the test data. The training
data is same as the analysis data. Table 5 shows thesize of the test data. Here, we used the maximum
entropy method tool (Le, 2008) with the default options except “-i 2000.”In the evaluation, we obtained the recall, the precision and their harmonic mean, i.e., F-measure.
The recall and precision are respectively defined asfollows.
recall =# of correctly inserted commas# of commas in the correct data

precision =# of correctly inserted commas# of inserted commas

In our research, to realize automatic comma insertion with high quality, we analyzed each usage ofcommas and decided the features for the ME method
based on the analysis. To confirm the effectivenessof our features, we established the baseline method
as a comparative method whereby commas are inserted by the ME method in which only simple morphological information is used. The baseline method
uses the morphological information in Table 4 andthe information of the rightmost morpheme (a surface form) of a bunsetsu as features.
5.2 Experimental Results
Table 6 shows the experimental results of the baseline and our method. The recall and precisionwere 69.13% and 84.13% respectively, and we confirmed that our method had higher performance than

Table 6: Experimental results

recallprecision F-measureour
69.13%
84.13%
75.90
method (4,527/6,549) (4,527/5,381)
baseline
51.38%
70.90%
59.58(3,365/6,549) (3,365/4,746)

the baseline method. The percentage of sentenceswherein all commas were correctly inserted was
55.81%.
Figure 4 shows the comparison between the results of our method and the baseline method. The
baseline method was not able to insert commas rightafter the bunsetsu “浮かんでいるが (are floated)” or“決まらないため (not decided)” but inserted commas at unnatural positions such as between “名乗る
(calling himself)” and “副司令官が (the vice commander).” On the other hand, our method was able
to insert commas properly at such bunsetsu boundaries.

6 Discussion
6.1 Error Analysis
Among positions where commas existed in the test
data, there existed 2,022 positions where our method
did not insert commas. Among them, 862 wereclause boundaries, and the clause boundary “topicalized element-wa” accounted for 53.36% (460/862)
of them. There were a lot of clause boundaries of
the type “topicalized element-wa,” and the numberof commas inserted at such boundaries was large.
But, the rate of comma insertion itself was not veryhigh. We can say that the four features about “topicalized element-wa” did not always work well. Ta5

Phrases indicating the subject is a sequence of bunsetsus
consisting of bjk and all bunsetsus that are connected to bjk when
we trace their dependency relationship in modifier-to-modifyee
direction.

our method:
候補者として石原信雄内閣官房副長官や岩國哲人・島根
県出雲市長、鳩山邦夫前労相、作家の堺屋太一氏らの名前が浮かんでいるが、前提となる政党の枠組みが決まらないため、調整は難航。
(Nobuo Ishihara, the deputy chief cabinet secretary, Tetsundo
Iwakuni, the mayor of Izumo city in Shimane, Kunio Hatoyama,
the former labor minister and the writer Taichi Sakaiya arefloated as the candidate, however, since the framework of
the predicated political party is not decided, the coordination
makes little headway. )baseline:
候補者として石原信雄内閣官房副長官や岩國哲人・島根
県出雲市長鳩山邦夫前労相、作家の堺屋太一氏らの名前が浮かんでいるが前提となる政党の枠組みが決まらない
ため調整は難航。
(Nobuo Ishihara, the deputy chief cabinet secretary, Tetsundo
Iwakuni, the mayor of Izumo city in Shimane Kunio Hatoyama,
the former labor minister and the writer Taichi Sakaiya arefloated as the candidate however, since the framework of
the predicated political party is not decided the coordination
makes little headway. )our method:
マルコスと名乗る副司令官が表に出てくるが、実際の司令官は不明。
(While the vice commander calling himself Marcos appears
in public, an actual commander is uncertain.)baseline:
マルコスと名乗る、副司令官が表に出てくるが、実際の司令官は不明。
(While the vice commander, calling himself Marcos appears inpublic, an actual commander is uncertain.)

Figure 4: Comparison of the results of our method andbaseline method

Table 7: Result of comma insertion at the clause boundaries “topicalized element-wa.”recall23.46%(141/601)

precision
59.49%(141/237)

F-measure
33.65• our method:
ボウルに豚の背脂ニンニク、ショウガ、ネギのみ
じん切りを入れ、彩りの赤ピーマンも加えます。
(Put pork backfat garlic, ginger and shredded green
onion in a bowl, and add red bell peppers for color.)

In the correct data, a comma was inserted between
the bunsetsu “背脂 (backfat)” and “ニンニク (garlic).”
If a comma should be inserted right after the bunsetsu ‘‘背脂 (backfat),” the number of characters between commas would become too small to be judged
as appropriate by the proposed method. So, the feature about the number of characters between commas may have had harmful effects there. On theother hand, a comma was inserted properly between
the bunsetsu “ニンニク (garlic)” and “ショウガ(ginger).” This is because katakana characters appeared sequentially in addition to appearing as parallel nouns.
6.2 Unnatural Comma Insertionble 7 shows the results of comma insertion at theclause boundaries “topicalized element-wa.” While
there existed 601 commas at such boundaries in thetest data, only 141 commas were inserted correctly.
We need to consider more effective features about“topicalized element-wa.”
As for other cases, there existed 130 bunsetsuboundaries between parallel words where commas
were not inserted. One example of such case isshown below.
• correct data:
ボウルに豚の背脂、ニンニク、ショウガ、ネギのみじん切りを入れ、彩りの赤ピーマンも加えます。(Put pork backfat, garlic, ginger and shredded
green onion in a bowl, and add red bell peppers forcolor.)

When commas are inserted at obviously unnatural
positions, they have a major impact on the understanding of a sentence by readers. Here, we investigated how many commas had been inserted at obviously unnatural positions by our method. For thearticle on January 14th (217 sentences, 2,349 bunsetsus) in the test data, we examined 47 commas inserted incorrectly. Three persons decided whether
or not the inserted commas were obviously unnatural through consultations. Concretely, when all of
the three persons felt that an inserted comma would
make readers understand wrongly the meaning of
the sentence, the comma was judged to be obviously
unnatural.
Among 47 commas, 4 commas were judged obviously unnatural. This result shows that our method
is capable of inserting commas at natural positions
on some level.

Table 8: Comparison with human judgement

recall precision F-measure
78.30% 80.58%
79.42(249/318) (249/309)
our method 71.07% 82.78%
76.48(226/318) (226/273)
by human

6.3 Comparison with Human Judgement
In our experiment, we evaluated the results ofcomma insertion of our method by comparing themwith the correct data. However, the sufficient level
to be reached by automatic comma insertion is uncertain. Here, we evaluated our method by comparing them with the results of comma insertion byanother person. By using the same data as used in
the subsection 6.2, we conducted an experiment oncomma insertion by an annotator who was familiar
with writing Japanese documents. Table 8 shows therecall, the precision and the F-measure. The second
row shows the results of our method for the samedata. As the F-measure of the annotator was 79.42,
it turned out that comma insertion task was difficult even for humans. For F-measure, our method
achieved 96.30% (76.48/79.42) of the annotator’s result. Also, the precision of our method was 82.78%.
Although the comma insertion task is difficult, ourmethod was able to properly insert commas.

7

Conclusion

This paper proposed a method for inserting commas
into Japanese texts. Our method appropriately inserts commas based on the machine learning method
using such features as morphemes, dependencies
and clause boundaries. An experiment by using the
Kyoto Text Corpus (Kurohashi and Nagao, 1998)
showed an F-measure of 75.90, and we confirmed
the effectiveness of our method.
The analysis of the experimental results showedthat our method cannot insert commas of the particular usage. As a future work, it is necessary tofind more useful features for commas of this usage
and improve the recall of our method. Also, we will
examine “commas emphasizing the adjacent word”
which were not included in our targets.

Acknowledgments
This research was partially supported by the Grantin-Aids for Scientific Research (B) (No. 22300051)
and Young Scientists (B) (No. 21700157), and by
the Continuation Grants for Young Researchers of
The Asahi Glass Foundation.

References
Heidi Christensen, Yoshihiko Gotoh, and Steve Renals.
2001. Punctuation annotation using statistical prosody
models. In Proceedings of ISCA Workshop on Prosodyin Speech Recognition and Understanding, pages 35–
40.
Yuqing Guo, Haifeng Wang, and Josef van Genabith.
2010. A linguistically inspired statistical model for
Chinese punctuation generation. ACM Transactions
on Asian Language Information Processing, 9(2):6:1–
6:27.
Yoshihiko Hayashi. 1992. A three-level revision model
for improving Japanese bad-styled expressions. In
Proceeding of 14th International Conference on Computational Linguistics, pages 665–671.
Katsuichi Honda. 1982. Nihongo no sakubun gijutsu(Japanese writing skill). Asahi Shimbun Publications
Inc. (In Japanese).
Takashi Inukai. 2002. Moji hyouki tankyuhou (Method ofquestioning characters and notations). Asakura Pulishing Co., Ltd. (In Japanese).
Hideki Kashioka and Takehiko Maruyama. 2004. Segmentation of semantic unit in Japanese monologue.
In Proceedings of International Conference on Speech
Language Technology and Oriental COCOSDA, pages
87–92.
Ji-hwan Kim and P. C. Woodland. 2001. The use of
prosody in a combined system for punctuation generation and speech recognition. In Proceedings of 7th
European Conference on Speech Communication andTechnology, pages 2757–2760.
Sadao Kurohashi and Makoto Nagao. 1998. Building
a Japanese parsed corpus while improving the parsing
system. In Proceedings of 1st International Conference on Language Resources and Evaluation, pages
719–724.
Zhang Le. 2008. Maximum entropy modeling toolkit forpython and c++. http://homepages.inf.ed.
ac.uk/s0450736/maxent toolkit.html.
[Online; accessed 1-March-2008].
Yang Liu, Elizabeth Shriberg, Andreas Stolcke, Dustin
Hillard, Mari Ostendorf, and Mary Harper. 2006. Enriching speech recognition with automatic detection of

sentence boundaries and disfluencies. IEEE Transactions on Audio, Speech, and Language Processing,
14(5):1526–1540.
Tohru Shimizu, Satoshi Nakamura, and Tatsuya Kawahara. 2008. Effect of punctuation marks for speechtranslation unit boundary detection. IEICE technicalreport. Speech, 108(338):127–131. (In Japanese).
Shogakukan’s editiorial department. 2007. kutoten,
kigou, hugou katuyoujiten (dictionary of punctuations
and symbols ). Shogakukan. (In Japanese).
Eiji Suzuki, Shizuo Shimada, Kunio Kondo, and Hisashi
Sato. 1995. Automatic recognition of optimal punctuation in Japanese documents. In Proceedings of50th National Convention of IPSJ, 50(3):185–186. (InJapanese).
Michael White and Rajakrishnan Rajkumar.
2008.
A more precise analysis of punctuation for broadcoverage surface realization with CCG. In Proceedings of Workshop on Grammar Engineering AcrossFrameworks, pages 17–24.