Towards Machine Translation Using Contextual Information

A proposal is made for the use of con tex tua l info rmat ion in the machine t r ans la t ion of Japanese and English. This paper describes the use of a Context Monitor to nla in ta i l l con tex tua l infortmttion dyn,'unically and the ~tugmenlal ion of appropriate features to ~t semantic network to enahh~ simple inference. The al}proach taken is that {}t" "best gucs~? ' processing with the cont~extual information being hal~dled with semantic inf{~rmalion on ~ shallow level. 2 I n t r o d u c t i o n Current Machine qh'anslatiou (MT) systems proc,~ss input sentence by sentence. I[owever, experience wil.h English and Japanese has shown tha t some languages difl'er to such a degree tha t sentential translation y i e h l s p o o r r e s u l t s , l,eL us f irst c o m p a r e the r e su l t s of a conventional MT sysl.em with those we expect, t,o ge t for M T w i t h c o n t e x t : t . J::q'lJf]~-. _-i~¢{:¢/,? )[ b v,-)-1/~3-'. ~E~gfi £" 2)i L v, K 2. K-7: ~tlaJaS'd? ,l~ ~a ~t~. I;~y b t:: o 4. k c g ];! ( 5 ' ~ k o This might be t ranslated by a current, machine tl'anslation system as shown in Figure 11: It can clearly l)e seen tha t meaning in IHally seI/tenees is obscured. Let us compare this with I.he resuits of a system using simple cont.exl. ual informal,ion ms shown in Figure 2: This seco l /d t r a n s l a t i o n is i-tlllch Ill(H'(? CO]lO['{~ll{. ;IH{I better preserves the meaning of the original se,lten{'o. An a t t empt has therefore I}een made to solve some of tile problems of translal.ing languages SllCIt sis Japanese and English using contextual information. Due to [.he consideral.ions of wanting to produce a high quality small-sized MT system, lhe approach taken is to use tile resources awdlahle in an exisl;ing MT system and to process the contextu;d i,l['orlmd.ion l There is obviously n great difference in results Imtweet, systems, hnl, l.hese translat.icms relweSent tyl}iCal {uHe, llted) r~. stdts fi'om a numher of systems, a) and I}) options,hq}end on the default sett ings of individual systems 1. The Chief I)evel{}pment li;ngineer develot}ed two new TV models and Four new video ,nodels last year. 2. a) A vi{h'o was shil)ped to the Sales Section. b) We/Soineone shil)pcd a video to the Sales Seel, i o n . "I. a) ' l 'wo models were released straight away. l}) \ \ / e / ~ o l n e o n e released I,wo models straight a*,v a.g. d. It sohl very well. Figure 1: (jonventional M'P Results I. The Chief l)evelolmmnt Engineer developed DA'O IICW 'FV l l lode l s ~llld [()sir flew v i d e o n/oriels lasl year. 2. lie shipped the videos l.o t.he Sales Section. 3. They released two models straight away. 4. Tlmy sold very well. Figure. 2: Coutext, ual M'[' Kesults on a shallow level only, using the information gained to guide the translat ion on a "best guess" basis. This kiml of feal,ure with rat.her light; processing for the production of a higher quality t ranslat ion is desirable in a pracl,ical MT system because the advanl.ages of large-scah~ processing for deep conl.extual ilfform;d.ioi, are likely to he limited in Lids apl~lical.ion. 3 T h e M T S y s t e m The transhd, km system present,ed here is ;t model systent whidl is being used to investigai, e t, he techniques proposed. The translat ion Imr~ is carried out h, Pl{. O1,0(] usinp; nn l,FC-LIike gramma.tieal formalism 2. ']'he current, dictionaries conl,~dn information to translal.e aboul; 300 words. There are 350 grammar rules which (:own' a wide range of sentence pal,terns. The context monil,or operates using information retrieved from file f-sLrueturc of ;t SOlli.eltCe al't(W analysis. This ilfforlnal.ion is then used during the transfer 2'['[le cn'igimd lm,gl.anl for l;;hgllnh-Spanlsh iranslallcm deveh,p,,d I,y (1, Amm'es [:\m, wes'89] has been widely adapted and eldal'ged Io . I-I'; & E-J Iranslallon.