A CLASSIFICATION METHOI) FOR JAPANESE SIGNS 
USING MANUAL MOTION DESCRIPTIONS 
Hisahiro ADACHI and Kazuo KAMATA 
Department of Information Science, Utsunomiya University, 
Ishii-machi, Utsnnomiya, 321, JAPAN 
atlachi@gnrn .infm'.n t sm~mniyn- u.a('...i I) 
SUMMARY In this paper, wc prol~OSe a <:lassili<'ation method for sigus in ./ape<nest ,b'ig. I)(tngutqlC (JSI,). 
The metho<l is l>as<'d on I:\],c similaril,y I>el,wceun n+eH+nal .loli+Jtz dc.+i:rilJlion.+(M M \[)s) M' signs. M M l/s a~c the verbal 
dcs<:ripti<nm of signs, The measure (ff similarily I>ctw('en MM I)s is derivc<l from ihcir h,n#cst common subsc'quc+~c< 
(I,C,'-;) of MM I)s. liy (:Oral)u/inK fcal.urc vc(;\[ors of u propcrti(~s fr<)m a. linile sc.i of MM1)s and i)hUting them in 
the n-dimcnslonal I';u<:lidcau space, the similarity between signs can he r,'g;u'dcd as a.n internal angle I~el,',vcen Ihc 
vectors. '\['he result, of mH' experimenl is I,}l~I, I}le signili<:anl sign families can be obt;fin(~d, 
I. INTRODUCTION 
Stokoe (1960) is I.he lirsl, linguist I.o deal with the 
Sl;I;llC\[,llre Of signs in l.he S;lllle way as I,ha(, of oral words. 
lie uol:ed t.haI. I.here were three kinds of i~aramet.<!rs in 
de~cril>ing l, he sigu iu A mcri<a.,/ig, /..n.</u(tgc (ASI.) a.~ 
follows: ( I ) t, hc Ioca, l,i<m of qle signs rclal,iw~ I,o <,he body, 
(21) IJ~e haIM-shal)e <>f hau<ls involw~d in arl:iclda.l.i,g the 
sign a.nd, (3) the m<>v<!lucul, of hands. Oi.her linguists 
(li'rie<hna.n 1977, Battis<>u 1,q7;';) ha.vc claimed <,hal, a 
follr|,\]l paralneLer is ol>lip;al.ory, thai, is, the spal.ial ori- 
eul.al.i<m of the hamls rela.l:ive lo l.he body. In ./(tpane's~: 
.Ni/In l.anguaff((JSI,), a, few liuguisl,,~ ('l'a.nolcami 1979, 
Kanda 1982) took I:he similar apln'oaches, 
Thus, we m'ed I.<> ,specify th<, Ioc<dio,, h(utd-.~hap<~ 
movemcnl and ori6n, l(i.lio~ of lilt \[muds t<> describe 
t.he sign. Furthermore, il. is int.eresting 1.1> u<)l,c t.hal, a 
change in <rely one of l,I~<~ signilicam elem<mts iu hand- 
shape, local.ion, orient.ati<m and movement often results 
iu changing i.h<~ meauiug; (ex., antonym, synonym). The 
uotat.i<>n sysl.ems pr<q~osed I>y liuguisl.s <:au pr<wi<h" a 
very detailed aud broader reprcsmllatiou I,o describe 
signs. It is, hmvew~r, not easy l,o l:rallsforlii l.he siga 
iul.o the nol.al.i<m. For Mils r<'as(),: it, is 1.oo <<)st Io col= 
led; a large am<told, of sign data. 
C,msich'r, f<>r examph', a miuimal pair iu lhc move- 
mcul: as shown iu l"iK.\]. 
It is clea.r thai the nliIfimal pair { 'I:i\]~Y O~.nl.),q: 
O\[ 
I"i~ 1: The Minimal Pair of Signs (q:iJfi (a.m.), 'l:t~ (p.m.)) 
t~ (p,m.)/ mcaus the antonym senmnticaily a.ud repre 
s<mts I.Iw symmetry visually. Typical sign <licti<niary 
c<msist.s of ilhlstral.ions <,' l)hot,ogralflls aim t.h<" wM)ai 
descril)l.i<m.',, we called the descripti<ms m.an,ual mot~o.n 
dc.scriplions (MM I)s) represented as l;exI, written in nat= 
ural language. 
It can be considered thai; a. MMI) represents iul'of 
llHll,iOII exl,r~qc|,cd frOlll ~1, s0ri0,,s of the l\[lallllal /noLiotts 
of I.hc sign. 11. is not <lilIicult to find the symmetry o\[' 
signs by the c(mt.rast t>ef.ween tw<> MMI)s. lV<u ' c'×a.ltl- 
I>le, the toni.fast <)t' wor<ls '~i (right) aml ~F= (left,) can I>c 
ol)I.ained \['r<mL c(mll)ariug MMI)s of-'t:~ (a.m.) wil.h /l: 
~2 (l>.m.) a.~ foll<wvs. 
.~if-(I)X.~.'~+~ ,l'+f~+ ~'/::Cc"~¢ia~,l,'~::+,'C'C, f ~::fl19 g:@ 
We d<!,~<:rihe a. classificali<m reel;hod for sigu,s using 
mat.h<~nlatical tcchlfiqm.s ha,sod on I.he similarity b<" 
l,ween M M I)s. 
961 
2. DATA STRUCTLTRES FOR MMDS 
This section descril)cs l,hc rema, rl¢ablc characteristics 
of MMI) and a tra.nsfc, rmat.ion met.hod ddvd from 
l, hetn. The method i~icans l.hat MMI)s can he tra.us- 
fornted into I,he n-dhnel~sio\]tal /'eal:ure vectors. 
2.1 Tim Re.markat)le Characteristics of MMDs 
MMI)s nwan a kin,.I of the verl)a.l d(,scril)lions of the 
sigti, which are written in Japanese hmgiuagc' and has 
remarkal)le characterist.ics as follows: 
• MM Its have tnot'e c(inslraint:s ,m synt,aclic pal,l,erHs 
alld wi)rds Lhall getteral ,\]al)alt(!s( + Solll,OliCl~s, Ill 
or, her words, t;here are some I,:hM ()f synLacl,ic pal,- 
terns in MMDs, 
~, \[n Japimese, syn(inytus at0 often marl,aM wit.h t,h(' 
COtlltl'lOtl ~'a,tzjl-cllara(:l,l~i!s. F()r exa, lllDle , each set, of 
words A - { ~','T=, g,~ ~', ii~,jT' }, 1~ = { +£-jD, 
:~1,+. -L5 A.,+c.Ju, Ip t.e, :~: +,~ .m,:~'m,/JQ~ } has a <:,umnot~ 1)ostlix 
ka?u'i-characl.er ~'- or ~'~ aud s,tmc, kinds ofsemant.ic 
groups ;it'('. COllS\[,\]'llC(,(~d by \[;ll(?lll such aS 
~ 4i " ~" (Hg\]tl h.ol+d) 
=~-(hand) ~ lilq T + (b:.ft h~+?+,d) 
I, k- P. (1,,>~\]+ ~ ......... ~.~) 
+Jh' (fM.s;ev) + { 
'J" ' \]~' (little fi +q¢r) 
Thus, the combitmtion (if ka,:ji-charact;ers means se- 
mantic concatcqla.t.iotl. Sat o (1992) has als(t 1)oiut.d out 
them in his papt'r. 
2.2 Transfi}rn).atioll into F,tmt'ure Vectors 
To represcttt the (list.ril)ution of words ma.thetnat- 
ically, it is convenient, to considered as poh++t.s in the 
.-dimensional Euclidean Sl>;ice. The coordinates of 
poitfl.s can t)e given as the ~'>,./imc'usioual fl~ature vec- 
tors. Then, an infernal a.ngle llel.'.,vc:en the veer.ors can 
I>e considered as tim similarity t)ctwecll tJle worlls. In 
this case, l)rol)ez'ties of the feature vectors need t.o tuany 
poinl.s of view. (i.e., word frequency, part. of specch, 
CO-O(XqlI'I'OIIC(t I'Olal, iC)q, ~ltl(\[ SO (/It). \]ti l)al,t,(',rlt recogni- 
I:ious, the sam( + al)l)rC, a ches I tave nm(\[(~ use of recognizing 
l)ictures and let, tl~+rs Therefore, we ,%+;o seh'cl t;his al>- 
prr)ach which is sigt~.s art' F, lott:(~d in the ,-(limensiotutl 
li',ucli(leau SlmCC.. I"eal.url' vrctors <:ah hc ()l)tained hy 
cotlstru(:ting a Ill\]ire stal.e a.ut.omal.on a.ccel)ting MM l)s 
as fc, llc, ws. 
It. is well known that: limt.e state aul.(m,ata rec(tg\]lize 
tinite st.a.te la.ngua.ges (see Aho,A.V., el; al. 197'1). If 
a class of i)alt.erns can I,e de.scribed in a liuite st.a,.e 
l,~l, llgtl;I,Ir0, ;I \[\[t£il;e st,aLe &lll;otl'\]+l,|,Oil (:;Ill 1)¢! (X)\]ISLI'I\]CI,I'(I 
to recogltize MMI)s ilcscril)ed this class of l)atteruls. 
Exmnl)l,u.2.1 
Let A=4'i~.0)g~~'\]L~ {-.I.-Y'+, I~,=,\]~!:\]~(\])~J~J'~: I-'PY'7~) 
and (~=iil,jr\]'=c\])/J',t:~ ~ \[lilt-J* 7+ be MM Its. The lit\]ire sl.at, e 
(,l'a.llSi|,iOll diagram ot' a a.ut,otua.t,otl acCC.ltting the set, of 
MMD is shown in Fig. 2,2. 
~iT.a) I=+)+ Z., 
.... +"----~O " '.___t%© 
Fig '2: A \]i'inil.e Stale q'ransit.ion Diag, ia+m 
Then, a regular exprc'ssion derive(I from I.he al)/)ve 
diagra.m is shown l h0 fi)l\]owing. 
I!\]ach ka~¢\]~- or" kana- character of the almve reg\]ilar 
c×pressiot£ cau be considered as i)roperlies (,\]1 I;h0 J'l?;i- 
tm'e vectrors for Ishe sigr,. The feat.ur(~ vect.ors for t.ho 
sign derived fro\],\] MMI)s arc. shovvu iu Tal)le I. 
+,, \],+ ,:,:, + ++ it, +++ + ,- ,,-,,, 0,+ + 
A I 1 0 l 1 1 0 0 I I 
(~ ) 1 I 1 ) l l I 1) (J \[ l I 
Table 1: The feature vector:-; deriw.d from MMD 
Thus, l.hc signs can be rcl)rcseut.cd as l~-(lhneusiotud 
l+eat, m'e vect,:m'+;, w}|\]ch call })e (leliued as b+/ re+tots 
\[0,1\]. 
Furthermore. we can find a Mud ,:>f +ynt.actic pat.t.crn 
+- ?) - ~" -, where. - m(>aus variabk+s (tulun,verl),...), 
and (¢) (no)and ~" (it)o) nwall case t\]larkers. 
962 
3. SIMILARITY BETWEEN SIGNS 
This se,::|i(m describes how a situilarity t)etwe(!u signs 
is cotttpul.ed. To conq)ut.e sintihu'ily, we inl.ro(luc0d l\]+e 
Io+Ig+,sl-commo'n-sub,+cqu+ n( ( ./)+++clio, (I,(1~). 
3.1 Similarity he|;ween MMI)s 
The resull, of the I)revious ,:tiscussi(,us (:au I:,(, suln+ 
ularized a,q foll,::.vs: 
I, Similarity lml.wcen two signs ca:n I)c c(msidored as 
similarity hetweeu t.vvo MMI)s. 
2. Whc'u ,:h~.scril:,ing si~n,s matheumt.i,:ally, il, is ccmve- 
uien(, t.o rcgar,.l t,ltc'lU as l)()ili\],s ++t' \['e,~d,llre ~,'(~(Tl,()lis 
iu (.lie n-dimeusi,:mal I'~uclideau .-+l>aCe. The simi 
larity measure hetweeu l.wo signs i~ c<>usMered a.'-; 
+t,1! #tll~\]O ()f I,WO Vectors. 
3. If a \[initc state aul.oumla acc(!iH.hl ~ .MMI)..+ curt he 
(;OllSl,rllc'l:e(\], \[)ro\])Ol'lri(L'+; Of f(!3,l,l|l'U V('¢I,()I'B (b~tli \[)(+ 
placc(\] all ch,+tracl.er.~ (:Ollgl,l'llCl,ill~> +"vim l)s. 
l,e(. ,I -: (~+t,+t..~ ..... (t,~) aad 11 :: (bl,l:~ ..... b,) l)o 
pl-dill\]CllBiOllal \['(++lllll'e Ve( t,(H':-; ()1" ,++;iglt~, Then, l, he Bitlli- 
larity tt.~asure l+elv.'e,~m sigus, dcm,t,ed, hv ,";(A, 1¢), cau 
lw delinc'd as f.lh+ws: 
I)l!',t". l:The Shnihu'ity belweeu t"eal.u re \:+.<:t,cm, 
5'(A, /~) : cos20 - (A,I~) "2 (1) 
II:~ll:+llnll + 
(0 < ,':>'(+4, n) 5-i t) 
where (A, l\]) is lh~+ inner pro(hu'l ol + wwt,ors A arid I'h 
attd can be cOtUl>Uled a,'+; fi>li+>ws: 
P+ 
k=l 
+I,411 :+ i.~ u..qq+t(l.+F(:d \[¢+'ClidC(~Pg '107"7' +,f v,mtor A aud 
C;III \])C c<+)tulmted as fr>It,,,',,+: 
t + 
N~,,,~<,,+, IIAIF ,:~,,, t,,+ ,:,,,,u.,t,,>d +,+ ,,h,, ~,.,~, .+' m - 
l i t ~ V<~(:tP+ + I' :~ l (+'r~ , I I ) ~:+~ I ~ I > <" COmlml.ed as the +tun o\[ + 
,++: A bi - I iu feature ve<:t.¢>rs A aml H,. 
II,ecall t.he feature w'ctm's of TaMe 1 itt th0 last sec+ 
~.~o,+. IIAII + ,.+,,, \[+,+ deliued a~ a hmgl.h ~+1' MMI) relat.ed 
t. w~<:l,t," A. In the same way, (A, II) ,::au t'.! ,:Mil,e,A 
a~ a leugi:h ~+1' a Io:,.:i,.,,I torn're.on sul~seque?~ce of MM l)s 
.'ehtted I,c> vcc't.rs A and IL We shall discus.s il. h+t detail. 
3.2 13cmgest (~Olllll|Oll S'ul~se.qu..~m.<',~ 
A s,tl',scqtwuce ol + a given sl.ring is al~,y si.riug ot>- 
l,ained by delet.ittg zero m' more sylubcds from tim giveu 
st.ring. A Io,gcsl +o+nmov subsequcn+~ (I+(JS) c+l' t.wc, 
st.rings is a suhseqm+t~ce o\[' bot,h l.ha(, is a.,+; long as a.uy 
ol,hc?r ('O/lllllOll SIIIISCCIlII+IICC. 
An h('+S vnea.ns tha.t the muuher of ttlatchithg char+ 
;,el.ors ccnl.~idez'iug l.he ch;m~cter uMer c<m~l.raint. Ig,' 
examlde, fl' X = abcl;,doh and Y :: l;d+aba, then all l+(IS 
c.f X aud Y in fiche, and has leugth 4 as shown m Vig. 3. 
't'lw othc.r l,(~S of X aml Y arc 6dab aud k+'ab, aud also 
haw' leltglh ,1. 
X- a h ~ h d ;,, b 
t t I t 
Y =: h <I <: ;)+ b ;~. 
l"i~ 3: Au IX',S of X aud Y 
Let. A - aj:++...(+.+ :+rod 11 = blb~...b, be sc+quenci!~. 
l"or a given ~equcuce .\" ~ xtx~...xt+ we deline IJie ith 
prelix of X , fur i := 0+ 1,...,/, as .\++ -- .l:j;c..+,...+:~. l;'or 
exanlple, if X =- abr:d+, t.hen X:+ - abe au,.l ,Y¢) is the 
empty sequence 't'he,~, au I+CS ,A" A and \[.i, <lou.tcu I)y 
L(:,~'(A, H), ca.n be cOlUlmled eIl\]ciett(,ly as the follow- 
ing recursiw, f,:n'ttmla u~iu~ I)yl\],+mti(" I>r'ogi'alt~tuil~g (\['or 
\['url.hox dclail,~ uf h(IS, see Thomas II, et. al. 1991). 
I.(:,'+'(\]t, t~) = c(.,, ,,) (+2) 
._ :c(i- l,j-1)-+ 1 if.i=b#, 
c'(~, j) t 
max{9(i,j.. I),c(/- l,j)} i\['c, i j-b# 
vvttere ('(i,j) is i.he hmgi.h of" an I,(:S of the s(:quc:twes 
Ai aml l~. Ifi ~ 0 aud/orj :+ 0, l+heu e(i,j) -: O. 
963 
44 J} h d c a. I) ;t 
0 0 0 1 1 I 
1 I 1 1 2 2 
I I 2 2 2 2 
1 1 2 2 3 3 
I 2 2 2 3 3 
I 2 2 3 3 ,I 
I 2 2 :l I ,I 
Tal)le 2: Tabh" I.{} C.(}mt)ul.{? L(IS (}l' X and Y 
The result, of computing I,(',S is shown as follows. 
D)rnlally, let; A = Ola2...om &lid 1\] = bil%..b,, be 
MMI)s. Then, S(A, tJ) nt{'nti{>u<xl I)revi(}usly can l)e 
defined as folh}ws: 
I)EF.2: The silnila.rily l)eiwc,en M M I)s 
LC>'{ A, l~ )'-' ,~'(A, ,) - (:~) 
Iltll 
((} </':;(A, B) < \] = £(A,A)) 
'rhlls~ w(2 Ii¢(:d lt(}l; {.o ('OllSl.l+llCl; 8 linil;e sl41l.C all- 
i;(}niaton a.ccel)l.ing a set (}\[' MMI)s and {.o l.ra.nsfornt 
fl'Olli MMI)s to featm'e ve(:l.ors. 'l~h(!ref(}re, the simila.r- 
ity COml),tta.t.ion based ou t,he I,CS is siml)h'r a,d easier 
{.hall Lhe COlllptll;;l|.ioll \]}{q.W{~()ll t.he veer.ors. 
Batagelj (1989) descrit}ed that 5,'(A, H) have I.(} sat.- 
isfy l.he following two c{}nditions. 
I. 5'(A, H) = 5(/L A) 
2. >'(/~, u) < :.,'C/t, A) o,. ,s'C,.t, u) >_ ,'.,'CA, ,~) 
Ot}viously, the above sinfiM\]'ily rneasurc satisties 
thern. 
3.3 An Exl,{u'inmnt 
We now show res,lll.s (}f all eXl)erin,eut, and verify 
t.hc situilarit.y measm'P t}el.weett signs. W(' used daLa it, 
The Illaslrat+d h'i.qn l)iclwnary (Maruyama 198d) for 
the following reasons. We ma(D use lhe sinq)le (lescrip- 
i.ion data. (1,527 entries), whM, were r{m(lered machine 
rea{labh> dal.a. By mergin.g t.he same MMI)s, itt ad- 
vauc{', 1,51/1 entries were ol)taiu('.d ~. For exatuF, le, ::}"~ 
6ii (name) a.ud /~'2 5;" (I)a.dge) iu Tal}le 3 t,teaus k,'(g, ii?i 
, \]+; 'y ".2;') = I. 
l i.e., IlS()d l}ai.lm'n tn;+Ichlng c+mun;:mds awk mid sed (m \[ iN IX 
Tim resull.s of an eXl)eriu,ent say {,hal, t, hc similarii;ics 
of36 pah's are grcal.er tha.t~ 0.8 and 570 pairs a.re grcat.er 
than 0.5. 
sign.A 
{}..{}T l.'J, i:~ (aft,.,+) 
0.96 ~g l,V~ (glad) 
{).,9:~ f+~j < (w,,,.k) 
{}.9l 0," ft! (woma, n) 
(}.90 U '? "~" (eml,letn) 
0.88 T~-(da, xght.a,') 
0.8s 2-~'. d (,~a ............... t) 
0.88 ~,,~(hltr()duce) 
0.87 T~77 (comp;u'e) 
0.86 ~(evidmu:e) 
{}.84 i021. ~,~ (.,,;a) -- 
u.8,1 I:g% (go 'm) 
0.83 ~iI{ ( I}ack ) 
0.83 i~:) (hesitate) 
0.83 \['" (\]mMw) 
il(~{ (Y,N{,ha.,,~a) 
sign, B 
D,'95 (beshle) 
~- I.v~ (happy) 
{1:'~ (.ion) 
9J t!1- (re;m) 
YK~ I}\[I (.,a+me), / <'y "7 (hadge) 
{ ..... ) 
(in~.provemem.) 
(hfl re'prefer) 
/ ¢5) ,'/" .X .H (balance) 
.~ (p,o,,0 ~) 
@5 (climl)) 
P,\] (inside) 
iIOJ~;P, {,.,,.',,~,l) 
l-. (top) 
ff't 6 g' (~r~.,IJ,) 
Tahle 4: An 1'2amph' for Minimal I'airs of Sil,s 
{ l,msitler, for exa.mph,, parts oft,he apF, roxiumte shH- 
ilar pairs as shc, wu in T;d)le 4. A l)ah' {//J;t (daughMr), .&l, 
:" (.'~o,O} u,ea:,s l,he a.Umy., +u,d i,l:,: oil,or pair { 4!i L. 
~,~' (s,'./), ~; < (c'ry)} means the syu(utynl, Thlm, t, hese 
r(su/t,s meaus I,hat t,he m(,mbers of a siluilar pair have 
ill(? ('OIIIlll{}ll S(qIKlIlI.i(' COlllpOlll~lllL |11 eft.her w,~}r(is, hy 
,:x}mpul\]ng lhe similarity o\[' MMI), miuinlal pairs {)\[" 
sig;.qs can I)e obi,ained. 
The sin,ilarity of mamufl mot.ions results in the si,ll 
ilarity of meauing, which is a kiml of sigu rormatiw> 
units. That is, a miuima.l pair //1:4 and ,~,f" have a com- 
mon seiHant.ic C(}lIlI)OIl(qlI; children of parents such 
as a mot,ion a hand is moved the forward related 
to the body , ;I,II(I ;Ill hl(lividlla\] S(qll~lll|,ic COlll|>o 
IR'nl the female or male sex such as usin A a little 
or thuulh finger. 
'l'hcr(' are. howcvc,', a fi'w ,:XCCl)t.ions in t,hc ahow~ 
rule. For exanlple, each of a pair { f6'~fl~ (Yokoh(mm), i'P} 
C.'/.P (:-;?;'moth)} hav,~t differ<'nt meanhig, lint both o\[' 
them are de.rived fl'Ol'll t,hc Salll(~ iconic iilOI.iOll {)\[ \[,li(? 
ohjecg "t'azors". From the lauguage pragmal+ics I:,oiul,s 
of view, the imt',ort;ml, thiug is that a meaning of sigus 
dlallgeS ill various COllLOX{ just. ;-is a Ii/(Nlllilig o\[' ~1 W{}P(\] 
"sI',ring" chang('s iu various COllI.cxl., 
The pohlt we wish to, cnfl>hasize is that, COIII\[}III 
964 
ilig l,hc' sittiihu'ily h(!t,w(?en MM I)s resiilis th(! sigllilicaul, 
iiliniliial pair of sign, 
Fig '1: ,qiglls of ~1:4 da.ghl(r) ai.l ,/h, J" (s(,t, 
C SS ,' " '' ) ~" O 4. A ,I,A.~ ~ 1\[ ICA 11( N ME \[ H 1) 
4.1 Maf.heniat;i<:al N()t;ion 
For a liuil(,set X, a hilmry rclatio, h'(X,X) Ihai, 
is rc./le:r*l,(, ,'+y?nm+l'r+c a?/d lran.sili+,( is calh'(I all cquiv- 
alri~c<' rdo/Zom For each rlctii(!nt a: lit X, we d(!filio a 
sol A .... which rolll,ahis all l,\]io (qOlilVlll,'. o\[ .\" l,hiil arl' 
relal,(~(I l,o .c I)y 1,11o oquival(!ilC(' i'(@ll, i(lll, \],'oriiially, 
A.,.-: {:,;l(.,:,y)< \],'(X,)':)}. 
A,, is chmrly a suhsct ,:d' X. Th.:' elcilleili .r is il,sclr 
contained in A,. due 1,o l,lw rc~\[Ic, xivit,y of t'I,; I',~callse II, is 
i,r;insil,iv(! all,el S.yliilti(!l,ri(', oath rlilqtili(!r o\[ .,~:,. iS rolal,ed 
I,o all llie oLlicr iileiiii)Vl'S of ,4 .... This s(q A;,: is rol'erre(l 
I,(t ;is an t~qulvah~llCe (:lass ()\[ \]l'(.\', .\') wii, h rcsl)(Wl Io 
,r. The Family ()1' all s.ch ('(i.ivah'.('(' cl.ss,~s deli.(~(I I)y 
I,}io r(~lal, ioll, which is ilSllally (l(.nol(M hy .\'ll(, \['l)rlllS ii 
l)a.rl,illOil OI1 X. 
4.2 A Classilicat;i<m M(;t;h()d 
Wr (lcscrihc how (:hisl,erhig a giv(;u finil,e set +)f' signs 
iisiiig the siiiiilaril,y ill(~a.gllr(, pr()l)()s('d hi ~(!cl, ion :/, Th(' 
shililat'ii,,y r(,htl,iou 5,'(A, 11) satisfies Ihv \['oi\[owiilg two 
('()ll(lit iOllS, 
• r(,Ih~xiv,,: ,V(A, A) .... I 
• syli,il.q,ric: H(A, H) :-: ,",'(b',A) 
.b'(A, l~), howev(w, (I,:)(~su'l sal,isfy th(! Lransitiw ~ c(m 
dii,i(m. The., we i.t,rod.c(~ I, hc following iu(!q.alii,y, 
,s'(A, H) p ,,,,,×,,,h,(.S'(A,C+),,<;(C ', n)} (4) 
EXallq)h~ 4.1 
I,(% X - {(l, b. c, d, +} I)(' a set of sighs, and X x X - 
{m(,,, ,,), ,v(., I,), ,<.'(., ,:) ...... '-:,'(<,, ,,)}. 
The similarity rehH,iott ,S'(X,X) ran I)e r(q)r(~,~(ml,ed as 
t,h(' I'<:.l\]owi.~ similarity nta.irix S. 
B\[ +~. h c d <+ T ;,~ b c d e 
,:,~;F (~.e o7, ().:~ (i:s ~ I o.:~ o.7 o.:~ (-).~ 
h .2 1 0.3 0.5 0.3 h 0.3 I 0.3 0.5 0.3 
(: (10.5 0.3 1 0 2 0,7 (: 0,7 0.3 l ().:~ 0.7 I,) 
d ,:/ 0.5 0.2 I 0 2 (I ().3 0.5 0,3 l 0.3 
el().8 ()+:1 0.7 0,2 I :::,'> e (),8 0.3 0,7 (:).3 l / 
,<"; call l)e l, ra.sf(wnve>d hH,() l, he al)ovc l+ransit.ivr ma. 
t, rix T h.y a l'ormuht 
v'(A, H) :: ,,,.× ,.i,,{,s'CA, (:), :+'((', .'~)}. 
T a e c <1 I) (:1 
a T (;.-~ t\[77 0.3 (~'~ a T ( 0:7 
0.8 I 0.7 {).3 0.3 e 0.8 0 
0.3 0,3 0+5; I 0.5 d I 0+5 
h \[o.3 0,3 tLS; 0.5 1 --~ h |0.5 1 
'\[' can L.' lnailsform(,:l iul,:) I,he othor matrix by a 
Itia.l,ri× sort,in<K op(!ral,i(n, whMl i'e;trratlg(' the atl,ril>,m.s 
accc.rding i. l hoir c()t'r(qal,i(m c.elli,:'ienL'-;. 
Thus, ;t srt, of I h(" si~. carl h(, classili.~d .sing thu 
l',ariil, i(m in,.hlc(.d hy tit(> eqtfivahmcc, rc.lali(n, ~/',, wii,h 
the apl)rol)riate thrc.,-;hohl c, ( 1 > ;~> 0 ). 
x/:ti+.~-- { \[,,,,:\], ~,, (~, ~, }, 
.v/% ,~ { \[,.,,+',d, a, t, }, 
x/'ti>,+ :: (\[.,,,. <,\], \[<L ~,\] ), 
.Vl:/i,,> -- Xl'/h.:, = { \[., <, ~., u, I,\] }. 
(lotmcqucul,ly, for every monot(mi('ally decreasin~ li 
0 ), the k-h'vcl hierarchy ('lusl;crs in the form of a den- 
drogranl can hc .hl,ained as shown iN Fig 5. llowevrr, 
\[,O ( Oll,~i,l'll(:\[ i,h(, (\]Cllth'ogl'alll is iioi, ol|r \])l'cs011L purpo,~e. 
The rca,~o, is l,hal, tim shuilarity measure 5'(A, B) has 
a l~ml, urc ()f the curve cos ~ 0. That is, as the. simila,ril, i0~ 
965 
a.re close the nmxinmm ( S(A, B) = 1 ), gains of noise 
factor (i.e., inflection ) can be ignored. 'l'hcreforc, The 
low-level clusters ( < 0.5 ) are nol. necessary for our 
purpose. \¥e want. t;o find the significant sign famili('s 
than I.o obtain hierarchy si;rucl.lu:es. 
o.8 o_ lo.  o.,\] o.~ o.a ~ Oi~lO.~ o.~ / 
5 \]\[0.3 0.3 0.3 
0.5 
Fig 5: The k-level hierarchy clust, crs: de~.drogr'a*'~ 
4.3 An gXl)erilnent 
To nmke discussions SilUl)lcr, wc used the sample 
(la.ta. of MMI)s (\]29 entries) including two key-words 
(chara.cl.ers) of K\] (mouth) 71 (ml, ries and ~-~ (lips) 58 
entries; I)eca.us(L a. wor(I t(~. call be idmlt, itied wil.h a word 
1£71 in Ja.pa.ncse la.nguage. \Vc wanted 1.o obtain the re 
sull.s from oxtracl.ing sign families rathc'r than I.o obtain 
t.he hiera.r(:hy structure or th(! form o\[ a dendrograln. 
The purpose of classilications is l.o focus (m th(' mini- 
nml lmirs of signs. 
By merging the identical (lata I.hat. nmal,s 5'(~4, l~) = 
1, 129 cntri(>s a.rc merged into 101 entries. The total 
amount of sign pairs satisfying N(A, B) >_ 0.6 are 25 
p;drs, and a 3\[ × 31 similaril.y matrix is ot)i.ained. Th(m, 
the simila.rity ma|,rix is l.ransformcd into a (.ransil.ive 
lnatrix, and the cquiw:denco classes C}1.11 I)C ol)(,}liiio(l ~Is 
shown in Tabh> 6. 
We classified given signs (129 cnl,rics) into 11 chlst,(>rs 
a.nd ibund tha.I, tim la.rgesl, am(toni, of sign family is 3, 
'v~ (REl))-fa.mily as Follows: 
23 entries : at:: (red), g (st.r.~twl)c'rry), Jk{~ (h(red- 
il.y), FI I1~{tl (Sundty), ,)~.£e}g (tire), ~3.~ (('.xprc'ss), U > ~" 
(~,.pp>), ~r~ta~ (im)od), ;,,.t s(, o,,. 
This sign family has an essential common MMI3 " 
~'iT:a)X)?-~t:~'CY I-k~-lzgS-c-C~T//,a'31 <" a.nd motion in 
Fig.T, and has senmntic COIllpt'ql(~:ll|. " \['Od': . 
jlenn 
31) 
#@$~@ 
#$ 
Fig ~: A 'l~'a,sit.iw, Matrix 
Fig 7: The M MD a~,,d Mothm of ~Jl~Ircd) 
966 
'l?ha.t is, .;~'f/2 (hc.redily) dcrivod \[l',)lU "bh)c,d", II Ilt'il 
l\] (Sltttday) deriw~d frc, ut the red UUlueric in the cahm- 
dar, and Jg3?~ (exl)ress) derived \['rotu I.hc' red-,stamp cm 
the letter, and so on. 
Consider, flw example, a. family of sigus { +'l'?~:, "7 "- 
X, C_ /~ .1: 5,/;\[f:'~'? .(', i"~'U~ } n,eans {sall+J, Worcestc'r- 
sa'+l.cc, p+ per, red - paper, a.sl ri?+gc+lL }+ The l'aufily has 
:-m essetd;ial COIIIIIIOll SCIII;IIII,ic ('()lll\])oIt(qll,, which III(?;IIIS 
"not sweet"relweslmled a:-+ ct'<>ok.iug all ,:~1' \[iitgel'S. 'l'he 
,:\[ifli+retwe of a. pair( 'i'?U "~ (salt.y), i"'~U" (astringeul))is 
wh('ther t.u hc rut.at.cd ur ul> and down. 
IBc0 gl +p :I~ +b -,J++ 
(j)m4~ ,'a+:th: +1 ~t~ ~:;¢i+-5: 
Fig 8: Signs of '??b~ (salty) and ?t~x+~ (astringcnl.) 
5. CONCLUDING REMARKS 
We' haw~ pr~q~osed a new chtssiii,:'aliou reel.hod J'<)I' 
signs in .ISL. The tnethod is has,~>,.l c,u tlw simihu'il.y 
between the' wMml descril)tions oI: sign+'-:, called Me~u- 
'ual Molio~ Descriptiou (M M I)). The siluilarity of sigus 
<:a.t~ be cot~sidc'red as a.n internal a.ugle I',ei.we,m \[i"a.- 
ture w'~cl.ors rel+resel~te+<+l as 1mints iu t.he n-dimc+usi,:mal 
I!;u(-lidea.n SF, a.c~.. By (;Otnl'ml.ing fl':at.ure~ vecl.c, rs of ?~ 
i)rol;,erl.ies from MMDs and Idol.tiug theut iu the 'n+ 
dimensional l!;m:lidean SF, aCe, an augle hetweei~ two ww- 
turs c;m hc cc, ttsMered as l,he similarily bc'l,weeu lhl' Lv./o 
sigus. As a chtssilicaiiuu nl('l.h,:~d, wl' have iut.roduced a 
\[iuilc' set of sigus divided imo cqnivalcncc class~,s ul~ th<' 
equiwfllm,::e relation with the. k h.v,:.l. 
As fm'l.lter research directi,ms, we will apF, ly t.his 
simila.ril.y measure t.o the rc'tricval c,f the simihu' signs iu 
Sig, Elcclr+mic l)icliouarg (SEI)). Whet~ '.vc lo(ik at at, 
tlll\]ittW',Vll Sigtl, if t.h,, sigll IlIol,ioll +llHtge (+all I'~(' l+el'Jre - 
setlt,ed usiug the \[\)rtu ,)f MMI)s, lh+e I:,~,st matdwd sign 
~r the +.;igl~ I'amily cau he ret,ri,:wed by cC, mlmting tim 
similarity amoug a giveu MMI) atv:l MMI)s ,:d' sigus iu 
gel). 
ACKNOWLEDGMENTS 
x, Ve would like 1.,', thanl~ 1.o l)r.'t'akeshi Kltmaga.i I'm' 
reardillg l,h,e manus,::ril)l and tuakittg a. tmml)er ,~)l' helpful 
sttggesLions. We' Slmcial tha.uks are due Io a. lmlAisher 
I(l(-l)ai~a'm.zk,~:u ,5'craz+ \[ilr i>eruiissiou to rel)r~)<luce il- 
h~stratilms in llh+..sh'atcd Si(+pt l)ictio~tary \[10\]+ 
REFERENCE 
\[1\] +"4tok<m,W.(J: A Dictio~+ar:+j of American Sign La~+- 
g~tag~ o7~ L~ng+t.islz~ l'rit~ciplc.s, Linstol+. I'rcss, t gcis. 
\[2\] l,'riedtuan,l,.A: 7'h,+! n+mtt&.stal~o~ of s.uhj+cl, object 
and Iopzc it+ Am+r~ca~l ,5'iy~ Language, 
Academic Pt'css, 1976. 
\[3\] I~a.l.tisou,l't.: L~:~:ical borrowt~g in Amcrh:a~+ S~gu 
Laluluag¢. I,instok \['tess, l\[)78. 
\[4\] Kyle..I.(l. ;rod WolI,IL: Sign laT~y+tacje "l',l~c .study 
of d,.f p~oph aTId /hczr lang+tage, 
(Mmbl'idge IJniver~il.y Press, 1985. 
\[5\] T.+mokami,'l'M+.ashi. et al.: ?,'yluwa n, Scka~, NIl li 
Press,l!179 (iu .lapauese). 
\[6\] Sa.to,Sal.oshi: (.'7'M.'An I';J:a'mple-lla.s~ d translation 
A id 5'gstcm. Proceedings of (,'()JAN("92, I \[)92. 
\[7\] I),atagelj,V.: ,q'imilaril.u \]t,leasures between ,h'h'uc- 
htrcd Obj~cls, MATII/(;\[II"M/(:()MI' 198,8 
((',raoww,A. I,;d), Elsevier, F,1~.25-39, 1989, 
\[S\] Aho,A.V., ll,:)p,::roft.,.I.l';, and Ulhnalh,l.I).: 
7'he I)~:.sigt~ a+~d AT~+l.Ii.si,+ of (:ompul~r Ahjor'ithms, 
.Addis(m \'Vesley, 1974, 
\[9\] '\['hCmms II, el. al: lu.lroduclion to Algorilhml.,+ , 
F,p.:~14 320, MIT Ih'ess, I.+-)91. 
\[10\] Maruyaum,l';oji. I!M: IIht.sh'atcd Sign I)*cliouary, 
KK-I)aiv+autikku Seraze, 
1984 (in ,lapauese). 
\[1\]\] llarl.igau,.I.A: (Tu.sh.ri~+y Algorithms, 3ohu Wiley, 
1971. 
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