From: Proceedings, Fourth Bar Ilan Symposium on Foundations of Artificial Intelligence. Copyright © 1995, AAAI (www.aaai.org). All rights reserved.
The Future of MTis Now
andBar.Hillel was(almostentirely) Right
EIliott Macklovitch
Centrefor InformationTechnology
Innovation(CITI)
1575 Chomedey
Boulevard
Laval, Quebec,Canada
1.
Introduction
A seer, accordingto onedictionary definition, is a personwhocanpredict eventsor
developments;
someone,
in other words, whocan foretell the future. As far as I know,
Yehoshua
Bar-Hillel never actually claimedto be a seer. Hewasfirst andforemosta
scientist (a logician andphilosopherof science),not a prophet.But in his manywritings
on machine
translation in the 1950’sandearly 60’s, Bar-Hillel did makea number
of clear
andimportantpredictions about the future of MT;andbaseduponhis assessment
of what
waspossiblein the field, he suggested
certain priorities for future development.
In this
paper,I shall summarize
someof the morestriking of thoseearly predictions andattempt
to evaluatethemin light of the currentstate of the art of MT,some
thirty-five yearslater.
Asthe title of mypapersuggests,I believethat Bar-Hillel’s predictionshavebeenlargely
borne out; andyet his suggestionsfor morereasonablewaysof putting the powerof
computersat the service of translators havegoneby andlarge unheeded.In the final
section of this paper;I will describea systemcurrently underdevelopment
at the CITI
called TransCheck,which is a novel kind of support tool for humantranslators. The
approachto translation automationthat underpinsTransCheck
is wholly consistent with
Bar-Hillel’s owncall for a modestandjudicious useof mechanical
aids as an alternative
to classical MT,andas suchI amquite confidenthe wouldhaveendorsedit. At the CITI,
weare convinced
it is the wayof the future.
Q
Onthe Nonfeasibility of Fully Automatic,HighQuality Translation
(or FAHQT)
Thecelebratedargumentthat Bar-Hillei publishedin 1960on the nonfeasibility of
fully automatic,high quality machinetranslation is nearly as well-knownas the acronym
he coinedfor it, andcertainly doesnot bear repeatingin extenso.As Bar-HUlelhimself
pointed out, the argumentdoes not even concern translation proper; rather, it
demonstrates
the inescapableneedfor extra-linguistic knowledge
in order to determine
the meaning
= andhencethe translation - of a polysemous
wordlike "pen" in a perfectly
innocuoussentencelike "Theboxis in the pen". As it turns out, the knowledge
required
Mackloviteh
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From: Proceedings, Fourth Bar Ilan Symposium on Foundations of Artificial Intelligence. Copyright © 1995, AAAI (www.aaai.org). All rights reserved.
to disambiguate
"pen" in this context concernsnot just common-sense
expectationsabout
the relative sizes of writing instrumentsandchildren’s enclosures;also requiredis the
ability to reasonaboutthis knowledge,
viz. if an object X is in someotherobject Y, X is
normally smaller than y.1 Thesekinds of reasoningcapabilities andextra-linguistic
knowledge
wereobviouslynot available to existing machine
translation systems
thirty-five
yearsago. Moreimportantfor us today, however,
is the manner
in whichBar-Hillel reacted
to the suggestionthat suchinformationmighteventuallybe put at the disposalof later MT
systems:
’~¢Vhatsucha suggestionamounts
to, if takenseriously, is the requirement
that a
translation machineshouldnot only be suppliedwith a dictionary but also with a
universal encyclopedia.This is surely utterly chimerical andhardly deservesany
further discussion."(Bar-Hillel [2], p.176)
Still, Bar-Hillel did accordthe suggestion
somefurther attention, elaboratingon why
he consideredthe idea of equipping an MTsystemwith a universal encyclopediaso
preposterous.
"Thenumberof facts wehuman
beingsknowis, in a certain very pregnantsense,
infinite. Knowing,for instance, that at a certain moment
there are exactly eight
chairs in a certain room,wealso knowthat there are morethan five chairs, less
than 9, 10, 11, 12 andso on, ad infinitum... Weknowall theseadditional facts by
inferencesweare able to perform,andit is clear that they are not, in anyserious
sense,storedin our memory."
(Bar-Hillel [2], p.177)
At the core of Bar-Hillel’s argument,
therefore,is not just the fact that translation
routinely requires encyclopedicknowledge;i.e. knowledge
not about the properties of
languagebut aboutthe real world. Rather,the nubof the problemis the fact that humans
caninstantaneously
accessinfinite amounts
of suchknowledge,
as a result of their ability
to infer. Andwhile Bar-Hillel wasable to envision a translating machinethat might
eventually performcertain inferences, he found it inconceivablethat such a machine
would be able to do so in the same spontaneous manner or under the same
circumstances
as anyintelligent human
can, andas translators unconsciously
do all the
time.
All in all, Bar-Hillel’s celebratedargument
coversno morethana pagein the original
text; andyet there are at least two quite different waysin whichit canbe interpreted.On
the first andnarrowerinterpretation, it is a logically impeccable
demonstration
of the
unattainability of FAHQT,
seennot as a strawmanbut rather as the actual, thoughoften
unstated,goal of manyof the groupsworkingin MTat that time. For the purposesof this
demonstration,it is not necessaryfor Bar-Hillel to quantify the frequencywith which
I. Hence,given that boxes are generally larger than writing instruments, the box in question is most likely within a
kind of enclosure, such as a playpen.Barringindications to the contrary, this at least is a moreplausible interpretation
of the sentence than the one in which"pen" is a writing instrument.
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sentenceslike thoseof his simple exampleoccurin various types of documents;
as long
as anyinstance of this kind of ambiguityappears,requiring extra-linguistic knowledge
and/orreasoning
for its resolution,it is sufficient to scuttle the fully automatic
part of the
FAHQT
ideal. In other words, as soonas a human
post-editor has to be called uponto
resolve the ambiguity of one polysemousword like "pen", the MTsystem involved
necessarilybecomes
less than fully automatic.Moreinterestingly, perhaps,oncethe need
for humanintervention in the translation process is admitted and accepted,one can
envisagea widerangeof possiblemodesof cooperation,or divisions of labour, between
manandmachine.To find the mostproductiveor cost-effective arrangement
was,for BarHillel, an empirical questionthat demanded
careful study. Unfortunately, it wasnot a
questionthat seemsto haveinterested the majority of MTworkersat the time, manyof
whomcontinued to confuse the aims and methodsof MTas an area of fundamental
researchwith thoseof MTas a practical endeavour.
Bar-Hillel recognizedthe validity of
both pursuits; whathe deploredwastheir confusion.Wereturn to this issue in section 6
below.
3. The Future
of MT
Thereis anotherpossibleinterpretation of Bar-Hillel’s famousdemonstration,one
that is broader and morepessimistic, in which he can be seen as arguing for the
unattainability of FAHQT
not merelyin the short term,but altogether.Thatthis in fact was
the real intention of his argument
is suggested
somewhat
passinglyin the original article,
whereBar-Hi,el states =that no existing or imaginableprogramwill enablean electronic
computerto determinethe meaningof the word"pen" in the given sentence..." (p.175;
emphasis
added).But he reinforces this interpretation andmakesit perfectly clear in
piece he publishedin 1962in the TimesLiterary Supplement,
entitled =TheFuture of
MachineTranslation." In it, Bar-Hillel declares that "MThas reachedan impassefrom
whichit is not likely to emerge
withouta radical change
in the wholeapproach..."
"...with all the progressmade
in hardware,programming
techniquesandlinguistic
insight, the quality of fully autonomous
mechanicaltranslation, even when
restricted to scientific andtechnologicalmaterial, will neverapproachthat of
qualified humantranslators and therefore MTwilt only undervery exceptional
circumstances
be able to compete
with human
translation." (Bar-Hillel [3], p.182;
again, myemphasis)
Tojustifythis pessimisticprognostic,Bar-Hillel points to the syntactical(or scoping)
ambiguityof the adjective in a simple phraselike "slow neutronsand protons." The
examplehe choosesis different, but in essence,itis the sameconciseargumentas he
invokedin the celebrated1960article, basedon the fact that human
translators routinely
makeuse of their vast backgroundknowledge,no counterpart of which he says could
conceivablystand at the disposal of computers.Bar-Hillel leaves it to the reader to
Macklovitch
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From: Proceedings, Fourth Bar Ilan Symposium on Foundations of Artificial Intelligence. Copyright © 1995, AAAI (www.aaai.org). All rights reserved.
generalize the argumentto the "innumerablesemanticalambiguitieswhichnothing but
plain, factual knowledge
or considerations
of truthfulnessandconsistency
will resolve..."
(ibid [3], p.182).
Thefinal conclusionsBar-Hillel arrives at in ’~he Futureof MachineTranslation"
musthaveappearedapocalyptic to MTworkersat the time; those of the ALPAC
report
pale in comparison:
"1 would say that there is no prospect whatsoeverthat the employmentof
electronicdigital computers
in the field of translationwill lead to anyrevolutionary
changes.
A complete
automation
of the activity is whollyutopian.... Thequickerthis
is understood,
the better are the chances
that moreattentionwill be paid to finding
efficient waysof improving
the statusof scientific andtechnological
translation-...
including judicious andmodest
useof mechanical
aids." (Bar-Hillel [3], p.183)
4. The Future is Now
It hasnowbeenover thirty yearssince Bar-Hillel publishedtheseprovocativeviews
on the future of machine
translation. Of course,the future is by definition boundless.
But
suppose
wedecidedto call in the bets today,andarbitrarily decreed
that the future is now.
HowwouldBar-Hillel’s predictionsfare in light of the currentstate of machine
translation?
In particular, someof the questionswewouldlike to considerare the following: WasBarHillel right in declaringthat high quality andfull automation
are almostalwaysmutually
exclusive in machine
translation?2 Hastime shownthat he wascorrect, or just short of
imagination, in asserting that no imaginableprogramwouldever allow a computerto
perform sensedisambiguationson polysemouswordslike "pen" in underdetermined
contextslike that of his famousexample?
Is it reasonable
to characterizeas exceptional
those attested cases in which MThas been able to competefavourably with human
translation? Moregenerally, has machinetranslation yet emergedfrom the impassein
whichBar-Hillel sawit miring in 1962?Andfinally, has anythinglike a radical change
occurredin the dominantapproachto the wholeproblemof translation automation,like
the oneBar-Hillel calledfor in the early sixties?
It is no easytask to attemptto summarize
the current state of the art in a field as
diverse andebullient as MTis today; andso inevitably, mypersonalassessment
will
appearto somepeopleas incompleteor tendentious.Still, it seemsto methat there are
certain indisputablefacts aboutthe current state of machinetranslation whichanyone,
regardlessof his or her particular bias, mustnecessarilyaccept.Andoneof theseis that
the growinguseof computers
over the last ten or fifteen yearshasnot beenaccompanied
by anythinglike the revolutionin translation that early MTpractitionershadhopedfor. On
this point at least, Bar-Hillel hasturnedout to be undeniably
correct. Whileaccuratedata
2. "Thosewhoare interested in MTas a primarily practical device must realize that full automationof the translation
process is incompatiblewith high quality." (Bar-Hillel [5], p. 167)
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on the worldtranslation marketare notoriouslydifficult to obtain, I amawareof no studies
or estimatesthat accordmachine
translation morethan 5%of that market-andthat figure
appearsto meto be generous.Whyis it that in 1995MTstill occupiessucha marginal
role in professionaltranslation worldwide?
Theunavoidable
answer,in myview, is that in
the vast majority of translation situations, currently available MTsystemsare simplynot
3 Andin mostcases, this is becausea
able to satisfy users’ needsand/or expectations.
significant gapcontinuesto exist between
the quality of the "raw" machine
output andthe
quality requirements
of the endusers, suchthat the cost of the post-editing necessary
to
makethe machine
output usableturns out to be prohibitive. Heretoo, it wouldseemthat
Bar-Hillel wasquite correct in assertinga generalincompatibilitybetween
high quality and
fully automaticmachine
translation.
Whatabout those cases whereMTdoes prove cost-effective and so can compete
favourablywith human
translation? Thesewouldappearto fall into oneof two categories.
In the first, the applicationdomain
is so narrowthat the developers
havebeenable to craft
a specialisedsystemcapableof producingtranslations of acceptablequality, principally
becausethe restrictions on the languageusedin the domaineffectively reducethe full
range of linguistic ambiguities to manageable
proportions.4 In the other class of
successful MTapplications, the end users agree to accept less than top quality
translations- either because
this is the only wayof obtaininga translationat all, or as a
cost savingmeasure
for texts that will not receivewideor public distribution. Overall,
however,the translation situations in whicheither of these two conditions obtains are
relatively rare, or as Bar-Hillel qualified them,"exceptional".
5.
MT and AI
Turningnowto the moretechnical questionof the capacityof current MTsystemsto
performlexico-semanticaldisambiguations
like thosethat Bar-Hillel illustrated with his
s
famous"box in the pen" example, let mefirst remarkhowappropriateit is that this
questionbe consideredat a symposium
on the foundationsof artificial intelligence. For
the issue raised by suchexamples
directly links machine
translation to the broaderfields
of AI and natural languageunderstanding.As mentionedabove,the knowledgerequired
to disambiguate"pen"
in Bar-Hillel’s example
is not primarily linguistic; rather, it involves
common-sense
expectationsaboutreal-world objects, as well as the ability to reasonand
3. Otherexplanationsare possible, at least in principle. For example,adequate
MTsystemsmightexist but simplybe
too expensivefor the majority of potential users. Currently, however,this is certainly not the case; on the contrary,
inexpensive PC-basedsystems have madeM’r morewidely available than ever. The problemlies in the deficiency of
the technology,regardless of whatone is preparedto pay for it.
4. Or, in the absence of naturally occurring sublanguages(like that exploited by Canada’sMETEO
system), artificial
restrictions nay be imposedon the languagein whichtechnical documentationis drafted, in order to simplify the input
to an MTsystemfurther downline.There has been an increase in the use of controlled languagefor MTin recent years.
5. Or, for that matter, syntactical disambiguationslike the one he illustrated with the "slow neutrons and protons"
example,since both require a capacity to reason over extra-linguistic knowledge.
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draw inferences over this kind of extra-linguistic information. Here, it wouldbe
disingenuousnot to acknowledge
the substantial progressthat hasbeenachievedsince
the early 1960’s.For onething, the mainthrust of Bar-Hillel’s argument
is nowa generally
acceptedtruth in the field: everyoneinvolved in MTresearch anddevelopmenttoday
recognizesthat in order to correctly translate unrestricted text, an MTsystemmustbe
suppliednot just with dictionaries andgrammars,
but with someportion of encyclopedic
knowledgeas well. Overthe last three decades,numerous
researchershaveattempted
to design MTsystemsin such a wayas to accommodate
this fundamentalfact about
translation. This is not the placefor an exhaustivesurveyof theseefforts; but wewould
like to attempta generalevaluationof their overall success.
Terry Winogradis a prominentpioneer in artificial intelligence, whoseSHRDLU
system
in the late 60’s is still cited as providinga striking illustration of naturallanguage
understanding.In 1984,Winogradpublishedan article in Scientific Americanentitled
"ComputerSoftware for Workingwith Language,"in which he raised the following
question:
"Is there softwarethat really dealswith meaning
- softwarethat exhibits the kind
of reasoningthat a personwoulduse in carrying out tasks suchas translating,
summarizingor answering a question? Suchsoftware has been the goal of
researchprojectsin artificial intelligencesince the mid-1960’s,whenthe necessary
computerhardwareand programmingtechniques beganto appear even as the
impracticability of machinetranslation wasbecoming
apparent..." (Winograd
[6],
p.136)
Winograd
briefly reviewssomeof the better knownNLPprojects in the 70’s and80’s
that attemptedto encodeknowledge
of the world in a form that a programcould use to
drawinferences(e.g. Schank’sscripts). Theproblem,he points out, is that all of these
programs
workonly in highly limited, somewhat
artificial domains,andit is not at all
obvioushow- or whether- they canbe extended.In his conclusion,the reply he himself
providesto his earlier questionis certainly not very encouraging;in fact, it is quite
reminiscentof the conclusions
that Bar-Hillel hadarrived at twenty-fiveyearsearlier.
’q’he limitations on the formalizationof contextualmeaning
makeit impossibleat
present - andconceivablyforever- to designcomputerprogramsthat comeclose
to full mimicryof human
languageunderstanding."(Winograd[6], p.142)
But doesthis necessarily entail that computerswill never be able to translate
adequately?Perhapsit might still be possible to design programsthat wouldallow a
machine
to producerelatively high quality translations withouthavingto simulatethe full
extent of human
languageunderstanding;if not all the time, at least often enoughfor
human
post-editingto be cost-effective. Actually, Bar-Hillel himselfthoughtso for a time.
Referringbackto the expectationshe first held for MT,he observed:
’I knewthen that nothingcorresponding
to items (3) and(4) [i.e. goodgeneral
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background
knowledge
andexpertnessin the field] could be expectedof electronic
computersbut ... entertained somehopesthat by exploiting the redundance
of
natural languagetexts better than human
readers usually do, weshould perhaps
be in a position to enablethe computers
to overcome,
at least partly, their lack of
knowledge
andunderstanding."(Bar-Hillel [4], p.213)
For Bar-Hillel, however,thosehopeswereshort-lived. In 1962,he wrote:
’9"houghit is undoubtedlythe case that somereduction of ambiguity can be
obtainedthroughbetter attention to certain formal clues ... it shouldby nowbe
perfectly clear that there are limits to whattheserefinements[of purely formal
methods]can achieve, limits that definitely block the wayto autonomous,
highquality, machine
translation." (ibid, p.213)
Other AI researchershavebeenless pessimistic than Winogradand Bar-Hillel.
Sergei Nirenburg, a Iongtime stalwart of the knowledge-based
approachto machine
translati.on, is oneof these. HeandKennethGoodman
publisheda bravearticle [7] in
1990, in whichthey systematically take up manyof the criticisms that are frequently
directed against meaning-based
(or interlingual) MT, andexposethe doublestandards
andmanyof the inconsistenciesin the argumentsthat are often employedto repudiate
and even disparage the interlingual paradigm. But in the face of widespreadand
persistent scepticism about the overall feasibility of developinga completeset of
language-independent
meaning
representationsfor all possible linguistic expressionsin
all humanlanguages,NirenburgandGoodman
can do little morethan protest that ’~qe
are makinginroadsinto theseandother difficult areas."(p.184)In the end,they are forced
to recognizethat the only real wayto silence the critics andconvincethe scepticsis to
demonstrate
the practical utility of the approach
by actually building a productionsystem
prototype.
Until suchtime as weseethe results of sucha prototype, however,it seemsto me
wehaveevery reasonto remainsceptical. For as Winograd
andothers havebeencareful
to point out, all the interlingual systemsthat havebeendocumented
or demonstrated
to
6
date havebeenmoreor less toy systems. To the extent that they have beenable to
simulatesomemeasure
of inferencingin order to arrive at a correct translation, theseAIbasedsystemsmayperhapshave shownBar-Hillel to be wrong, at least in a narrow
sense.7 Nonetheless,I doubt that Bar-Hillel wouldhavebeenvery impressedwith such
demonstrations. For though an accomplishedtheorist in other domains, he never
remainedsolely a theorist in matters of translation, but alwaysexhibited a genuine
6. As Hutchins [15] puts it in the summary
of his chapter on AI-basedMTsystems: "It needs to be stressed, however,
that none of the AI workersare expecting their workto result in the near future in ’operational’ MTsystems."(p.284)
7. Thougheven this is not entirely obvious. As mentionedabove, Bar-Hillel was able to envision a machinecapable
of inferencing; what he found more difficult to imagine was "a schemewhich would make a machine perform such
inferences in the same or similar circumstances under which an intelligent humanbeing wouldperform them." (BarHillel [2], p. 177) Andof course, he also discountedany ad hoc procedure, mountedsolely for the case at hand, "whose
futility wouldshowitself in the next example."(ibid, p. 174)
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concern with the practical problemsof translation in the real world. And here,
demonstrations
of the possibility of machinereasoningwithin toy domainsare of little
consequence.
Themajor obstacle to fully automatic,cost-effective machinetranslation
todayremainsexactly the sameas it was35 yearsago, to wit, the vast andunpredictable
rangeof the knowledge
that is requiredto allow a machineto achievean understanding
of a sourcetext that is sufficient for the purposesof translation. AsHutchinsandSomers
put it in their Introductionto Machine
Translation:
"Theproblemfor MTsystemsis that it is at presentimpossiblein practice to code
andincorporateall the potential (real world) knowledge
that mightbe required
resolveall possibleambiguitiesin a particular system,evenin systems
restricted
to relatively narrowrangesof contexts and applications. Despite advancesin
Artificial Intelligence andin computing
technology,the situation is unlikely to
improvein the near future: the sheercomplexityandintractibility of real world
knowledge
are the principal impediments
to quick solutions." (Hutchins& Somers
[8], p.93)
Hence,it seemsfairly safe to say that Bar-Hillel wouldnot havesubstantially
modifiedhis viewson the feasibility of FAHQT,
hadhe lived beyond1975to witnesssome
of the impressivesuccesses
in artificial intelligence. Withoutwantingto diminishthe
importof the advances
of the last twentyyears, it doesappearto be generallytrue that AI
andits daughterdiscipline MTare similar, in that their mostimpressiveapplicationshave
beenachievedin relatively restricted domains;
in both fields, depthof understanding
and
breadthof coverageremainby andlarge mutually exclusive. Moreover,Bar-Hillel was
alreadyfamiliar with some
of the early successes
of AI research,e.g. the workon pattern
recognition (or perceptrons) and programsto play checkers. Given his remarkable
foresight, wewouldbe rash to disregardthe warninghe formulatedin 1962:"it wouldbe
disastrousto extrapolatefromtheseprimitive exhibitions of artificial intelligence to
something
like translation." (Bar-Hillel [4], p.214)
6. A Radical Changeof Approach
In summary:
an objective assessment
of the state of the art in MTwouldseemto
suggestthat the field is still in fact miredin the same
impasse
that Bar-Hillel described
in
the early 60’s. Thequestion wenowwant to consider is whetherwehavebegunto see
anything like a radical changein the dominantapproachto the whole problemof
translation automation
that Bar-Hillel called for backthen. Myowninclination is to answer
in the negative(with an importantqualification, to be specifiedbelow).Althoughthey may
not publicly admitit, the researchers
on mostcurrentmachine
translationprojectsare still
striving to achieveFAHQT,
just as they werein Bar-Hillel’s time. Granted,the techniques
wenowemploymayhave evolved; newapproaches,or perhapswhole newparadigms,
haveemerged
overthe last decade,whichappearat first glanceto be radically innovative,
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e.g. Statistical MachineTranslation and Example-Based
MachineTranslation.8 But the
goal remainsessentially the samenowas it wasthen: to developa fully automatic
translating machine
capableof producingtarget texts of a quality comparable
to that of a
human
translator - in other words,a translating robot. Noonecan object to this as an
entirely worthwhilepursuit for a long-termresearchprogramme.
Theproblemis that many
of thoseworkingtowardthis objective continueto maintainthe unspoken
assumption
that
their researchefforts - evenif they do eventuallyfall short of their ultimate goal - will
neverthelessprove useful in providing short-term solutions to the practical problems
besettinga translation professionthat is overwhelmed
andunableto meetthe demand
for
its services.This is far froma self-evidenttruth, however,
as wewill arguebelow.In his
pre-ALPAC
articles, Bar-Hillel deploredjust this confusionbetweenthe aimsandmethods
of MTas an area of fundamental
researchandMTas a practical endeavour.Perhapsit is
time wefinally learnedthe lessonsof history andaccepted
the fact that classical MT-and
by this I mean
anyapproach
in whichthe initiative in the translation processis givenover
to the machineso that it can autonomously
producea target version of the sourcetext will never contribute morethan marginally to satisfying the ever-growingdemand
for
translation, or at least not for many,manyyearsto come.
For those whoremainconcemed
with the practical problemsof workingtranslators,
doesBar-Hillel indicate the direction he thought that a genuinelyradical changeof
approachshould take? The citation reproducedat the end of section 3 abovedoes
provideoneclue, whereBar-Hillel mentionsthe possibility of a"judicious andmodestuse
of mechanical
aids." (Herethe emphasis
is in the original.) In his "AimsandMethods
Machine
Translation"[5], Bar-HiUelis evenmoreexplicit:
’qhe only reasonableaim, then, for short-rangeresearchinto MTseemsto be that
of finding somemachine-post-editor partnership that would be commercially
competitive with existing humantranslation, and then try to improve the
commercialcompetitivenessof this partnership by improvingthe programming
in
order to delegateto the machine
moreandmoreoperationsin the total translation
processwhichit canperformmoreeffectively than the human
post-editor." (p.172)
A partnership betweenmachineandhumantranslator/post-editor that takes as its
starting point a judicious andmodestuseof mechanical
aids: this wouldseemto point to
whatis nowgenerally called machine-aided
human
translation (or MAHT),
as distinct from
9.
classical MTor human-aided
machinetranslation MAHT
has not beena popular avenue
of researchoverthe last thirty years. Tobe sure, it hashadits isolated champions;
most
notably, perhaps, Martin Kay (cf Kay [11]). But generally speaking, MAHT
has not
8. The standard reference for S/VII" is Brownet al. [9], and for EBMT,
Sato and Nagao[I0]. The former approach, of
course, does have historical antecedents, on which Bar-Hille! also had somevery interesting things to say. See
especiallyBai-Hillel [5], p. 17 I.
9. Again, the distinction between MAHT
and IIAMTmay be framed in terms of which of the two - manor machine
- retains the initiative in the translation process..In MAHT,
it is the humantranslator, and the machineis viewedas a
tool that maybe called uponto amplify humancapabilities, but only on such tasks that can be automatedreliably.
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succeeded
in attracting anythinglike the attention andfundingthat hasbeenpouredinto
classical MT,no doubtbecause,as Bar-Hillel suggested,the latter is perceivedas an
intellectually morechallengingpursuit. Onlyin the last few years, as moreandmore
researchershavestarted exploring corpus-basedapproachesto NLP,has MAHT
begun
1°
to receivethe attention it deserves. MAHT
is the philosophicalcornerstone
of the CITI’s
machine-aided
translation program.In this final section, I wouldlike to illustrate our
approachto MAHT
andbriefly discuss whyweconsiderit to be a radical departurefrom
traditional responses
to the problemof translation automation,by describingoneof the
translator supporttools weare currently developing.
Theproject in question is called TransCheck,
andit is documented
morefully in
Macklovitch [13]. As its namesuggests, TransCheckis intended to be used as a
translation checker,somewhat
like a spelling checker.But wherethe latter verifies certain
(orthographic)propertiesof a single monolingual
text, TransCheck
is designed
to validate
certain properties that normallymusthold betweentwo texts that are in a translation
relation. To do so, the systemincorporatesan alignmentalgorithmthat automaticallylinks
segments
(currently sentences)in the target text to their corresponding
segments
in the
sourcetext. Oncethe draft translation is completed,the translator submitsthe two
languagefiles to TransCheck,andthe systemthen verifies the aligned segmentsto
ensurethat they do not contain anydeceptivecognates,caiques,illicit borrowings,or
certain other commonly
occurring translation errors. Whenit does detect an error
describedin its database
of prohibitedtranslations, TransCheck
flags it andprovidesthe
user with informationon the correct target languageformthat shouldbe used.Preliminary
tests of the first prototype haveproducedencouraging
results, confirmingthe general
viability of a translation checkerbasedon a sentencealignmentprogramanda part-ofspeech
tagger;again,see[13] for further discussion.Ultimately,of course,it is hopedthat
TransCheck
will be able to detect moresubtle types of translation errors, andthat end
userswill be able to modifythe contentsof the databaseso that it reflects their own
translation norms.Here,however,I wouldlike to focus on anotherprojectedextensionto
TransCheck
which has not yet beenfully implemented,but whichillustrates, I think
particularly well, the interest of whatBar-Hillel called a judicious andmodestuseof
mechanicalaids.
Oneof the mostboring tasks for a translation reviser (whomaybe the translator
himself) is to verify that all numericalexpressionsin a sourcetext havebeencorrectly
renderedin the target. Textsin domainssuchas economics
or statistics can be packed
full of suchexpressions,andthe smallesterror in onedigit is tantamount
to a serious
mistranslation: not only is it extremelyembarrassing
for the translator, but it can
10. For moreon this paradigmshift, see Isabelle [12], wherethe author outlines someof the reasons whythe classical
rule-based approachto MThas producedso few useful results in the wayof translator support tools, and why,on the
contrary, the corpus-basedapproach seemsto lend itself so well to MAHT.
146
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From: Proceedings, Fourth Bar Ilan Symposium on Foundations of Artificial Intelligence. Copyright © 1995, AAAI (www.aaai.org). All rights reserved.
undermine
the credibility of the entire text. Thereasonwhyhuman
revisers find this task
so boringis that the "translation" of numericalexpressions
is so straightforwardthat it
requires almostno intellectual effort (althoughbetween
certain languages,there maybe
someminor differences of syntax); andyet every numbermuststill be checkedfor the
possibility of an error of transcriptionthat doesoccasionallyoccur.Is this not exactlythe
kind of mechanicaloperationfor whichcomputers
are better suited than humans?
Onthe
basis of the alignedsentencesit has paired, a systemlike TransCheck
shouldbe able to
verify that for every source segment containing a numerical expression, the
correspondingtarget segmentcontains the equivalent numericalexpression; andwhere
it doesn’t,that pair shouldbe broughtto the reviser’s attention. In actualfact, the problem
is not as trivial as I havesuggestedhere11;nonetheless,weare convincedthat evena
rudimentarynumericalcomponent
within TransCheck
should be able to validate a large
proportion of the numerical expressions in most texts. Moreover, an important
characteristicof this approach
to translation validation is that evenif the systemis less
thanfully exhaustive,whatever
errors it doesdetect will still contributeto improvingthe
quality of the final text; just asthe errors detectedby a spelling checkerimprovethe final
product, eventhoughnoneof those systemsis fully exhaustiveeither. Notice, however,
that this is not generallythe casewith classical MTsystems:the kind of partially correct
translations generatedby such systemsdo not always result in a reduction of the
translator’s workload,as manydisenchanted
MTusers havetestified over the years.
7.
Conclusion
TransCheck
is oneof a newgenerationof translation supporttools currently being
developed
at the CITI, all of whichare basedon the conceptof translation analysis, as
12 In our view, translation
opposed
to the classical MTapproach
of translation generation.
analysis doesconstitute a radical departurefrom traditional responsesto the whole
problemof howbest to automatethe translation process, although it is not as yet
anywhereclose to becomingthe dominantapproachin the field. In its favour, it has
allowedfor the development,
within a remarkablyshort period of time, of promisingnew
types of translation support tools, which are wholly consistent with the modestand
practical strategy that Bar-Hillel advocated
over 30 yearsago. Whetherthesetools will
actually live up to their promiseandprovemoreuseful to translatorsthan classical MThas
to date, only the future will tell. Andno onebut a seercanpredict the future.
11. Toillustrate just a fewof the complicationsfrequentlyencountered,there is the obviousproblemof numerical
expressionsthat are writtenaccordingto differentstandards,e.g. "7 p.m."vs. "19 h"; whichis whyall suchexpressions
will haveto translated into a normalizedformbefore beingcompared.Less obviously,the text in onelanguagemay
use a numeral,e.g. the date "1994",wherethe translation properly refers to the sameperiod by meansof a nonnumericalnounphraselike "last year".
12. SeeIsabelle et al. [14] for a descriptionof someof the CITI’sother projects, anda fuller discussionof the
differencesbetweentranslation analysis andtranslation generation.
Macklovitch
147
From: Proceedings, Fourth Bar Ilan Symposium on Foundations of Artificial Intelligence. Copyright © 1995, AAAI (www.aaai.org). All rights reserved.
References
[1] Bar-Hillel, Yehoshua.
Language
andInformation: SelectedEssayson their The0ry
andApplication, Addison-Wesley
Publishing Company,
Inc., 1964.
of the Nonfeasibility of Fully AutomaticHighQuality
[2] Bar-Hi,el, Y. "A Demonstration
Translation," reproduced
in [1], pp. 174-179.
Translation,"reproduced
in [1], pp. 180-184.
[3] Bar-Hillel, Y. ’’The Futureof Machine
Translation,"in [1],
[4] Bar-Hillel, Y. "FourLectureson AlgebraicLinguisticsandMachine
pp. 185-218.
in Machine
Translation," in [1], pp. 166-173.
[5] Bar-HiUel,Y. "AimsandMethods
[6] Winograd, Terry. "Computer Software for Working with Language," ~
American,no.251(3), September
1984.
"Treatment of Meaningin MTSystems,"
[7] Nirenburg, Sergei & KennethGoodman.
Proceedinos
of the Third International Conference on Theoretical and
v
MethodoloaicalIssues in MachineTranslation, Austin, Texas,June1990.
[8] Hutchins, W. John& Harold L. Somers.An Introduction to MachineTranslation,
AcademicPress, 1992.
[9] Brown, Peter et al. "A Statistical
L~, no.16:2, pp.79-85, 1990.
Approach to Machine Translation,"
~
Translation," EB.g.CB..(;;IJOg~
[10] Sato, Satoshi& MakotoNagao."TowardMemory-Based
of COLING-90,
vol.3, pp.247-252,1990.
[11] Kay, Martin. "The Proper Place of Menand Machinesin LanguageTranslation,"
CSL-80-11,Xerox PARC,1980.
[12] Isabelle, Pierre, "Machine-AidedHumanTranslation and the ParadigmShift,"
Proceedingsof the Fourth MachineTranslation Summit,Kobe,Japan,July 1993.
[13] Macklovitch,Elliott. "UsingBi-textual Alignmentfor Translation Validation: the
TransCheck
system," Proceedingsof the First Conferenceof the Association for
MachineTranslation in the Americas,Columbia,Maryland, pp.157-168,October
1994.
[14] Isabelle, Pierre et al. "Translation Analysis and Translation Automation,"
Proceedings
of the Fifth International Conference
on TheoreticalandMethodological
Issues in MachineTranslation, Kyoto, Japan,1993.
[15] Hutchins, W. John. MachineTranslation; P~t. Present. Future, Ellis Horwood,
Chichester,1986.
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BISFAI-95