Paraphrasing Honorifics
Kiyonori OHTAKE and Kazuhide YAMAMOTOATR Spoken Language Translation Research Laboratories
2-2-2 Hikaridai Seika-cho, Soraku-gun, Kyoto 619-0288, JAPAN{kohtake, yamamoto}@slt.atr.co.jp

Abstract
This paper reports on a paraphrasing method for Japanese honorifics.
Japanese honorific expressions, as seen
in real world dialogs, have many forms ofidentical meanings. This paper discusses
a paraphrasing method that simplifies
each utterance by removing honorifics.
To simplify an utterance, we take a practical approach: investigate a corpus, andconstruct paraphrasing rules that eliminate honorifics. We discuss how the constructed paraphrasing rules are effective
for the simplification of each utterance,
and a disambiguation method for somehonorific verbs that require disambiguation in order to be paraphrased.

1

Introduction

Honorifics are one of the characteristic propertiesof spoken languages. In general, it is said that
language is a communication tool, but this might
imply the transmission of intellectual information.
In fact, language conveys various information in
many ways, and it is here where honorifics play avery important role to express emotional information.
The processing of honorifics will be very important in the future, especially in the field of spoken language translation (SLT). This is because
the basic methods or techniques in SLT for practical communications will be more mature, necessitating the processing of emotional information toachieve more natural communications using translators in various situations.
In this paper, we discuss a paraphrasing method
for Japanese honorifics; however, it might also
be applied for Korean since Korean has honorific language that bears a striking resemblance
to the Japanese honorifics. For example, theJapanese expression koko ni aru (to be there) corresponds to the Korean yeogi issda, and one of its

honorific forms koko/kochira ni gozaimasu corresponds to yeogi isseupnida. In addition, Javaneseand Hindi also have honorifics that are similar
to the Japanese honorifics. Therefore, we hopethat our discussion of Japanese honorifics will contribute towards developments in processing honorifics for Korean, Javanese, or Hindi.
Japanese honorifics can be expressed by various
forms that are fundamentally the same in termsof meaning, to express one’s honor, respect, andother emotions. People utilize one of a numberof forms of honorifics according to the degree ofhonor or respect, addressee, or situation.
In processing honorifics, there are two directions: from ordinary form to honorific form andvice versa. The important point to remember
is that any one ordinary form and its honorificforms differ in formation, but both of them convey fundamentally the same intellectual information. Therefore, the most suitable processing ofhonorifics is paraphrasing.
In this paper, we discuss a paraphrasing ofJapanese honorifics that simplifies each utterance.
There are many honorific forms corresponding to
one ordinary form. As the first step of paraphrasing honorifics, we attempt to paraphrase honorificforms into their ordinary forms. If various honorific forms can be paraphrased into their ordinary
forms, the utterances become easier to process,both for programs and humans.
The simplification of honorifics is applicable to
SLT in various situations. In SLT, we earlier proposed a new paradigm that emphasizes monolingual processing for both the source and target languages (Yamamoto et al., 2001). This paradigm
attempts to resolve a majority of the existingtranslation problems by twin paraphrasing processes. The above two directions of paraphrasing
honorifics can be reflected in the twin paraphrasing processes: from honorific forms to their ordinary forms and the reverse can be reflected in theparaphrasing of the source language and that of
the target language, respectively.

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2

Honorific Forms in JapaneseIn this paper, we focus on the following five classes
as honorific forms, some of which were earlier introduced by Kaiser et al. (2001).
• Regular subject-honorific forms: formulations of verbs that exalt the subject of its
utterance.
• Regular humble forms: formulations of verbs
that exalt the object of its utterance.
• Irregular subject-honorific and humble forms:
irregular forms of subject-honorific and humble forms.
• Polite forms: polite formulations for nonverbal expressions.
• Euphemisms: forms that are used to avoid direct negative expressions or make utterances
more polite.
2.1

Regular subject-honorific forms

A subject-honorific form is an expression that exalts the subject of its utterance. There are two
types of regular subject-honorific forms. One iso/go- V ni naru, where V is a verb stem, andthe other is a passive form. Verbs that have special (irregular) forms do not usually have regularequivalents. In the structure o/go- V ni naru, V
is sandwiched between o/go- and ni naru. If V isa verbal noun, ni naru replaces suru. The choice
between the honorific prefixes o- and go- basicallydepends on whether the item the selection will attach to is native-Japanese (o-) or Sino-Japanese(go-). However, there are some exceptions, suchas o-denwa (telephone), which is Sino-Japanese.
Passive forms can be used as slightly less polite
honorifics. Examples of regular subject-honorificforms are as follows:
Ordinary form: anata ga ronbun wo kaku (Youwrite a paper.)utterance is watashi (I), who cannot be exalted.
The subject watashi should never be exalted inhonorific language.
2.2

Regular humble forms

A humble form is an expression that exalts the object of its utterance. The regular humble formation takes the form of o/go- V suru. The choice
between o- and go- is conditioned by the same
factor as mentioned above under Section 2.1. In
addition, verbs that have special (irregular) forms
do not usually have regular formations. Anotherhumble formation takes the form of o/go- V mousiageru. The form, mousiageru, is the irregular
humble form of iu (to say). However, this formation has the same function as the form o/goV suru. This formation gives us a more formal
impression.
2.3

Irregular honorific and humble verb
forms

A number of commonly used verbs that refer to aperson’s action are not used in their regular honorific forms; instead, a different ‘specialized’ honorific verb is used. Moreover, some honorific verbs
can be used for more than one action: meshiagaru
is used for both eating and drinking, and irassyaru
is used for coming, going, and being there. Accordingly, we have to disambiguate these honorificverbs when paraphrasing them.
Table 1 shows these irregular verbs (for slots
where no irregular verbs exist; regular formations
are given in parentheses).
Table 1: Major irregular subject-honorific andhumble verbs
Ordinary
Honorific
Humbleiru
irassharu
mairu‘to be’o-ide ni naru
iku
irassyaru
mairu‘to go’o-ide ni naru
morau
(o-morai ni naru) itadaku‘to receive’chōdai suruo/go- V ni naru form: anata ga ronbun wo okaki ni naru
2.4

Passive form: anata ga ronbun wo kakareru
There are some fixed expressions that look
like o/go- V ni naru, but are in fact not. In
other words, there are some exceptions of honorific forms that take the formation: o/go- V ninaru, but are not subject-honorific. For example,
watashi wa iroiro na hito ni o-sewa ni naru (Iam looked after by all sorts of people) has theexpression o-sewa ni naru, but the subject of thisPolite forms

So far, this paper has described honorifics of verbs,
whereas polite forms are non-verbal expressions.
To express one’s politeness, a person changes a
non-verbal expressions into its polite form. For
example, to refer to a person apart from title orpronoun, the person may use kata, the honorificequivalent of hito (person), in the singular and the
reduplicated katagata (persons) in the plural. An
example is taihen kenkō na kata da (He is a very

–14–

healthy person). The forms kata and katagata
are expressions without honorific prefixes.
In contrast, to express one’s politeness, a person attaches the prefix o- or go- to a noun that is
unlimited. In general, native speakers of Japanese
do not attach these prefixes to their own property.
Examples include, o-hashi (chopsticks), o-aji (thetaste), etc. However, some people always use theprefix o- or go- even when referring to their own
property. For example, watashi no o-saifu ga
nusumare mashita (My wallet was stolen). Honorific nouns of this type are called “beautified”
words in Japanese. The use of “beautified” words
varies greatly from individual to individual.
Not only nouns but also other words have polite forms. For instance, adjectives: yoi/ii (good)
has the form yoroshii, atsui (hot) has the form
o-atsui, etc.; and copula expressions: da has theform desu, and so on.
2.5

Euphemisms

There are a great number of expressions that seemto be euphemisms. By avoiding direct negative expression or employing euphemistic phrases, theseeuphemisms, indirect expressions, or periphrases
make utterances more polite.
For example, in some cases, Japanese negative
ending form nai can be expressed by the verbal
suffix kaneru to avoid a direct negative expression: hoshou dekinai (I can not guarantee it.)can be expressed by hoshou sikaneru. In othercases, various euphemistic phrases can be employed to express one’s politeness when expressing one’s thought, ask a favor of someone, etc.
Some examples of euphemistic phrases are as follows: kore de ii to omoi masu (I think thiswill be fine.), mado wo akete kure nai deshou ka(Could you please open the window?), and soon.
All of the expressions shown above are euphemisms. To raise the degree of politeness further, some other expressions are utilized. Oneof them is to make an introductory remark before requesting someone to do something, such as
sumimasen ga, mado wo akete kure masen ka(Excuse me, could you open the window?).

3

We can make many honorific forms from one
utterance to reflect the corresponding social relationships in the real world or emotions of the
speaker. For example, from the utterance “madowo akero (Open the window),” we can make“mado wo akete kudasai,” “mado wo akete kuremasen ka,” “mado wo akete itadake naidesyouka,” etc. From the examples shown above, we realize that honorifics are one of the features of spoken languages, and at the same time, they cause
an enormous variety of expressions.
If various utterances having basically the same
meanings could be made simpler, the utterances
could become easier to process, both for programs
and humans. At first glance, honorific language
may appear to have a rigid grammar. However,there are many exceptions or expressions that are
hard to handle as honorifics due to their being
idiomatic expressions.
In order to tackle this problem, we take thepractical approach of attempting to simplify andmake direct expressions. Before considering aparaphrasing method, we have to clarify the targets of the paraphrasing and to know what we willparaphrase. We first attempt to collect paraphrasing phenomena by replacing functional words asmuch as possible, by observing a spoken language
corpus. In this work, ATR SLDB (Speech andLanguage DataBase) (Morimoto et al., 1994) isutilized as the analysis target. This collection of
texts contains formal travel type conversations between two persons. The purpose of the conversations in the corpus is to acquire some informationfrom a clerk, or to claim something to a clerk.
Therefore, the dialogs include many sentences expressing the speaker’s emotions, questions, and intentions.
As a result of an analysis of the corpus, wefound that there are three types of expressions
that should be paraphrased.
1. honorifics
2. formal-styled language
3. phonemic changes
We discuss the paraphrasing of each expression in
the following.
3.1

Paraphrasing Japanese Spoken
Language

Japanese honorifics have a huge variation in expressions. The most typical parts of Japanese expressions are predicative parts. Therefore, spoken
Japanese has a huge variation in expressions compared with the written language.

Paraphrasing honorifics

There are many honorific forms in the corpus because the dialogs involve many kinds of questionanswer conversations, and there are many honorific expressions most of which are spoken by theclerk. All of the types we mentioned in Section
2 are included in the corpus. The real cases andtheir paraphrases are as follows:–15–

Regular subject-honorific forms: The expression o-tameshi ni naru (to try) should beparaphrased to tamesu. Regular subject-honorificforms also have passive-formed honorifics. However, we do not handle these types of passiveformed honorifics in this paper, since it is hard for
us to determine whether the passive form is used
as an honorific form or really as a passive form.
In addition, passive forms sometimes express thepossibility of an action, for example, mirareru (tobe able to see, to see, or to be seen) in yama wa
mirare mashita ka (Could you see the mountain?), yama wo mirareta no desu ka (Did you
see the mountain?), or dare ka ni mirare mashita(I was seen by someone.). Accordingly, we leavethis problem for our future work.
Regular humble forms: The expression oshirabe shi masu (I will check it) should be paraphrased to shirabe masu.
Irregular honorific and humble verb forms:
The expression ossyaru (to say) should be paraphrased to iu.
Polite forms: The expression o-isya san/sama(medical doctor) should be paraphrased to isya.
Euphemisms: The expression o-tomari negau
koto ga deki masu (You can get accomodations)should be paraphrased to tomare masu.
Honorific language seemingly has a very restricted grammar. However, there are a numberof exceptions, and many forms that should not beparaphrased due to their being idiomatic expressions. In addition, Japanese speakers sometimes
misapply a number of honorifics.
3.2

Paraphrasing phonemic change

Although there are few basic patterns in this type,they are frequent in spoken Japanese. A major
pattern is to change ‘no’ to ‘-n-’, as in shitano
desu (I did it) to shitan desu, where the former
expression is the normal pronunciation while thelatter is informal and colloquial. Another patternis the omission of ‘i,’ as in shiteita (I had been
doing it) to shiteta, also a normal to colloquialchange.

Paraphrasing Method

At the moment, and at least in the task of spoken
language paraphrasing, it is not the time to seek
the automatic acquisition of paraphrasing rules.
The reason for this is that, unlike tagging, parsing, and other natural language processing (NLP)
applications, the target and goal of paraphrasing
are unclear now. Moreover, the phenomenon ofparaphrasing itself in the real world is also uncertain. We plan to explore what we can do byparaphrasing first, rather than how we can construct paraphrasing rules.
Our paraphraser consists of two components:
a POS-based paraphraser and a verbal-featurebased paraphraser. The reason why there are twoparaphrasers is that rules for the POS-based side
are easily written, but the paraphrasing is limited. Therefore, easy rules and complex rules are
divided into two modules. In addition, we construct a disambiguation part due to some irregularhonorific verbs that require disambiguation.
It has been observed that most of the phenomena seen only in spoken languages change locally.
Considering this, we focus on the local changes of
linguistic phenomena into more ordinary expressions.
4.1

POS-based paraphraser

The overview of this paraphraser is as follows:
1. segment and part-of-speech (POS) tag by JUMAN1 , and parse (or chunk) by KNP2
2. convert to a labeled string (see Table 3 forexamples of labeled utterances)

Paraphrasing formal-styled language

Formal-styled language does not express the
speaker’s politeness, honor, and respectfulness.
However, from the viewpoint of reducing variations, we consider paraphrasing formal-styled language. The concrete cases are as follows: the expression (go-)iriyou (necessity) is a formal styled
expression of hitsuyou, the expression honjitsu(today) is a formal styled expression of kyou, andso fourth.
3.3

4

3. attempt to apply all of the paraphrase patterns once, in an order given in advance
4. repeat Step 3. if a pattern can recursively beapplied to the result of Step 3.
We first segment, tag, and parse the input utterance. We use its top hierarchy of the POS
system as it is. However, some labels are separated from the top hierarchy of the POS system
to meet paraphrasing requirements: verbal nouns
are isolated from nouns, suffixes are ramified under verbal, nominal, and numerical classifiers, andparticles are classified into four subclasses.
The results of the analysis are formatted to asequence of morphemes and their POSs, where one
POS has one assigned character as listed in Table1
http://pine.kuee.kyoto-u.ac.jp/nlresource/juman-e.html
2
http://pine.kuee.kyoto-u.ac.jp/nl-resource/knpe.html–16–

2 and chunking is expressed as spacing. Table 2
shows 20 POSs in all, among which 14 are originals
in JUMAN’s top hierarchy and six are ramified.
Table 2: Parts-of-speech and their symbols
a: adjective, b: copula, c: conjunction, d: adverb, e: sentence-final particle, g: nominal suffix, h: prefix, i: interjection, j: numerical classifier, k: demonstrative, n: noun, p: (other)
particle, q: conjunctive particle, r: attribute,s: verbal noun, t: verbal suffix, u: case particle, v: verb, x: auxiliary verb, z: symbol
The current version of the paraphraser is implemented by Perl. Each pattern is written in Perl ’s
substitution command s///. In total, there are
548 patterns, each constructed by hand, where one
pattern is one s///. Table 3 shows an example ofthe paraphrasing processing.
4.2

Table 4: Examples of disambiguation rules
target verb & clues
determined sense
target: ukagau
conjunctive particle ka
tazuneru (to ask)
tsuitekiku (to listen)sochira ni
iku (to go))target: irassyaru
dochira/doko kara
kuru (to come)
ima/genzai | atari/hen ni iru (to be there)

Verbal-feature-based paraphraser

The difference between the POS-based paraphraser and this verbal-feature-based paraphraser
is the target of the paraphraser. The paraphrasing rules by Perl ’s substitution command are very
easily written. However, these rules cannot easily
handle inflections of predicates, because to inflect
predicates correctly, we need to know the inflection types and forms.
We constructed almost 30 rules by hand, andshow some examples of these rules: if the utterance has a sequence: ‘o- CV kudasai,’ then it isparaphrased to ‘CV-te kudasai,’ where CV represents a continuous-formed verb and CV-te represents a te-typed continuous-formed verb. Concrete examples, in this case, are as follows: omatchi kudasai (Just a moment./ Can you holdon?) is paraphrased to matte kudasai, o tanoshimi
kudasai (Please, enjoy yourself.) is paraphrased
to tanoshinde kudasai, and so on. Another rule isthat if the utterance has a sequence: ‘VN shi kanemasu,’ where VN stands for verbal noun, then it
is paraphrased to ‘VN deki masen.’ A concrete
example is as follows: hosyou si kane masu (I can
not engage) is paraphrased to hosyou deki masen.
This paraphraser also segments, tags, andparses the input utterance like the POS-based
paraphraser. The paraphraser reads the parsed
utterance one by one, and checks all rules in anorder given in advance.
4.3

many disambiguation methods have been proposed and discussed (Yarowsky, 2000). However,in the field of disambiguation for irregular honorific verbs, there are some aspects different fromconventional disambiguation problems. The mostdifferent point is that the verbs that should be
disambiguated are limited to dozens at most. Accordingly, we take a deterministic approach towards disambiguation as an easy solution.
The disambiguation method utilizes a dependency structure of the utterance and some clues,
and then decides the sense of the verb. The
current disambiguation method examines whether
two chunks, that are the closest to the target verb
and depends on it, include some clues or not. Table 4 shows examples of disambiguation rules. We
manually constructed 18 rules for 10 verbs basedon SLDB observations.

Disambiguation for some irregularhonorific verbs

We mentioned in Section 2.3 that some irregular honorific verbs need disambiguation. So far,5

Evaluation

To evaluate our methods, we employ ATR SLDB,
which is our observation target in Section 3, as
the trained text set and ATR LDB (Language
DataBase) (Furuse et al., 1994) as the unseen
text set. The two corpora were independently collected, but both have the same domain and task,i.e., travel type conversations between two persons. Table 5 shows the number of dialogs andutterances of both corpora.
Table 5: Two corpora: SLDB and LDB
corpusSLDBLDBdialogs
618
1629
utterances 15425 35937

5.1

Evaluation Measure for Paraphrasing

Before reporting our evaluation results, we firstneed to discuss our evaluation measure for paraphrasing. To date, discussions on paraphrasing evaluations have been insufficient, since

–17–

0
1
2
3
4

Table 3: Examples of paraphrasinglabeled utterance (input format)
お h 支払い n の qt 方 n は pt いかが dt なさい v ます t か e
お h 支払い n の qt 方 n は pt どう kt なさい v ます t か e
支払い nの qt 方 nは pt どう kt なさい v ます t か e
支払い n は pt どう kt なさい vます t か e
支払い n は pt どう kt し v ます t か eparaphrasing research itself has practically juststarted.
We understand that we need to evaluate at least
two measures for paraphrasing in general:

Table 6: Evaluation results of paraphrasing
observed unseen
corpusSLDBLDButterances
1000
1000
paraphrased
745
770
unacceptable
1
8
paraphrasable
1223
accuracy
99.9%
99.0%
coverage
74.4%
76.2%
recall98.4%
97.1%• accuracy: how good (correct/natural/...)
paraphrases are produced.
• coverage: how many utterances are paraphrased correctly.
We should also consider a measure, unique forparaphrasing, that has the ability to determine
the following: how many paraphrases are able tobe produced. In this paper, however, we do notneed to employ this measure, since we discuss a
simplification by paraphrasing honorifics. Thismeasure would be utilized if we were to discuss
the generation of honorifics.
The two measures, the accuracy and the coverage, can be applied in evaluating the results of thedisambiguation. This is because each disambiguation result is very clear regardless of whether it iscorrect or not, since the disambiguation method
is based on deterministic rules and employs nolearning method. Therefore, we evaluate our disambiguation rules by these two measures.
5.2

Evaluation of paraphrasing

We randomly pick out 1000 utterances from each
corpus, and judge their accuracies. Table 6 shows
results of the evaluation, and also shows the number of utterances (shown as ‘paraphrasable’ in Table 6) that were not paraphrased but should havebeen paraphrased by the proposed method. The
number of utterances that should have been paraphrased enables us to calculate the recall shown in
Table 6. The coverage in the table shows the ratioof utterances that were paraphrased correctly to
all utterances, while, the recall is the ratio to allutterances that should have been paraphrased.
The number of paraphrased utterances shownin Table 6 does not necessarily express how many
honorifics were paraphrased. In addition, they include other non-honorifics that were paraphrased,such as phonemic changes.

applied patterns/ いかが d/ どう k/s/ お h 支払 n/ 支払 n/s/ の q (方 n| ほう n)//s/ なさい v/ し v/

5.3

Evaluation of disambiguation

We randomly pick out 100 utterances, which havepre-determined ambiguous honorific verbs, fromeach corpus. In addition, each utterance has
just one ambiguous honorific verb. We apply ourdisambiguation method, and evaluate the disambiguation results.
Table 7 shows results of the disambiguation,
where Rhuman and Rclue are defined as follows:
Rhuman =fhuman100 − fcomp

(1)

fclue
(2)
fhumanwhere fhuman represents the number of verbs that
could be disambiguated by humans, fcomp represents the number of verbs that could be disambiguated automatically, and fclue represents thenumber of verbs with obvious clues useful for automatic disambiguation in verbs that could be disambiguated by humans.
In other words, Rhuman represents how many
verbs were disambiguated by humans in verbs
that could not be disambiguated automatically,
and Rclue represents how many verbs had obvious clues (which were able to be mounted on thedisambiguation method) in verbs that could be
disambiguated by humans.
Rclue =

6

Discussions

The evaluation results shown in Table 6 prove thatthe method could paraphrase almost 75% of the–18–

orifics were included in SLDB. We counted thenumber of passive forms of “V + basic form of(ra)reru” from SLDB parsed by JUMAN and
KNP. In addition, we extracted sentences that included passive forms, and classified each passive
form into three groups: used as an honorific, used
as a passive form, or used as a potential verb form.
Results of the investigation are shown in Table 9.

Table 7: Disambiguation results
seen
unseencorpusSLDBLDButterances
100
100
disambiguated66
70
coverage
66.0%
70.0%
accuracy
100%(66/66) 100%(70/70)
Rhuman
67.6%(23/34) 73.3%(22/30)
Rclue
39.1%(9/23) 63.6%(14/22)

utterances with a very high accuracy. We cantherefore conclude that the paraphrasing method
is very safe, namely, it has vanishingly scarce side
effects.
From Table 7, we can state that the disambiguation method is also very safe. However, humans
could not disambiguate almost 10% (11/100 in
SLDB, 8/100 in LDB) of the utterances, and even
if they could disambiguate them in some way, almost 10% (14/100 in SLDB, 8/100 in LDB) of
the utterances had no clues for automatic disambiguation. From these observations, the possible
coverage of the proposed disambiguation method
is limited to almost 80%. The reason why humans
could not disambiguate about 10% was the lack of
information. In particular, the disambiguation ofverbs, such as irassyaru (either to come, go, or
be there) required information on the position between the speaker and his or her audience or athird person that was mentioned.
What is simplification by paraphrasing? Although we evaluated the paraphrased results onwhether they were acceptable or not, unfortunately we did not take any objective measure toevaluate the simplification. However, if we were to
introduce the number of chunks as a measure forsuch simplification, the results might be promising
as shown in Table 8.
Table 8: Paraphrasing results of whole corpora
name
SLDB
LDB
utterances
15425
35937
utterances paraphrased 11643
27148
chunks
77035 176030
chunks paraphrased
71462 161797

Table 9: Passive forms in SLDB
sentences in SLDB
15425
sentences including passive forms
407
passive forms
427
used as honorifics
241
used as passive forms
115
used as potential verb forms
49
could not classify
22
Table 9 shows that more than half of all passive
forms are used as honorifics. A considerable partof the results we could not classify was caused byparticular verbs: omou (to think), kangaeru (toconsider), kanjiru (to feel), and so on. These verbs
compose spontaneous passive sentences (Kaiser etal., 2001).
From a grammatical point of view, if a verb isa consonantal verb, then the passive form of theverb can not be a potential verb form but a reallypassive form or a subject-honorific form. This isbecause a consonantal verb has the original potential verb form “V + eru.”
On the other hand, if a verb is a vocalic verb,
the passive form of the verb can be one of the three
types. Sometimes, however, the passive form of a
vocalic verb omits ‘ra’ if the form is a potential
verb form. For example, mirareru (the passive
form of miru (to see)) can be used for a reallypassive form or a subject-honorific form, and theform mireru dropping ‘ra’ from mirareru can beused for a potential verb form.
From the discussion above, we may be able tonarrow the candidates of a passive form down.
However, to paraphrase passive forms correctly,
there are some other obstacles that have to besolved:In this work, we do not cover passive-formed
honorifics. To cover them, we need to examine
how to process them correctly and paraphrasethem adequately in future work. As a steppingstone to paraphrasing passive-formed honorifics,
we investigated how many passive-formed hon-–19–

• ellipsis resolution: In Japanese, ellipses areseen very often. As a consequence, if an utterance has a passive form, and the subject orobject of the utterance is omitted, the passive
form is hard to paraphrase.
• case frames: To determine whether a passive
form is a really passive form or not, high quality case frames are strongly desired.

7

Related Works

To date, there had been no work directly related
to the paraphrasing of honorifics. This is because
the methods or techniques in SLT or other NLP
applications had been premature. However, there
are some slightly related works.
Maeda et al. (1988) proposed a unificationbased approach to Japanese honorifics based ona version of HPSG (Head-driven Phrase Structure Grammar) for an experimental system thattranslates Japanese-English telephone and interkeyboard dialogs. They also discussed that many
human anaphoric references can be resolved byrecourse to pragmatic constraints on the use ofhonorifics. Unfortunately, however, they did not
discuss the domain or range of their approach, andthey also did not evaluate it.
Siegel (2000) presented a solution for the representation of Japanese honorificational informationin the HPSG framework for a machine translation system. The difference between Siegel’s solution and ours is whether the method assumes aframework, such as HPSG, or not. From a practical viewpoint, our proposed method does not assume such a theoretical framework but only shallow methods such as POS tagging, dependency
analysis, and pattern matching in Perl. That is
to say, a considerable part in the paraphrasing ofhonorifics can be done by a string level patternmatching technique, where the method assumes
only shallow level techniques like those mentioned
above.
In the field of paraphrasing for simplification,
Chandrasekar et al. (1996) discussed an approachof paraphrasing text by syntactical simplification,
based on the Finite State Grammar and a supertagging model. Actually, they have the same
motivation as us in believing that simplification isof great use for both humans and machines. However, their direction to simplification seems different from ours: they attempt to separate longand complicated sentences, whereas our target isto reduce variations spoken in the real world.

8

Conclusion

This paper discussed the paraphrasing ofJapanese honorifics by manually constructed
rules. Through an evaluation, it was unveiled that
our simplifying method can paraphrase over 70%
of all utterances with a very high accuracy (99%).
It was also proved that the proposed disambiguation method is very safe. However, the possible
coverage of this method is limited to almost 80%.
To disambiguate beyond this limit of coverage, weneed more information, such as the positions of
the participants.

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