Postgraduate Diploma in Translation

Postgraduate Diplomain Translation

Machine Translation I

Introduction to MT

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Outline

• Translation

• Machine Translation (MT)

• Why MT is important

• MT and the Human Translator

Why Translation is Difficult

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What is Translation?

• The process of transforming text from one language into a text in another language that is,

• in some sense, equivalent to that in a first language

• in some sense, a good text in its own right.

• It is what translators do....

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What Translators Actually Do:An Example of En/Fr TranslationAs recently as a decade ago it was widely believed that infectious disease was no longer much of a threat in the developed world. The remaining challenges to public health there, it was thought, stemmed from noninfectious conditions such as cancer, heart disease and degenerative diseases.

Il y a une dizaine d’annees, on croyait que les pays industrialises etait debarasses des risques lies aux maladies infectieuses et que la sante publique n’etait menacee que par des maladies comme le cancer, les troubles cardiaques, et les anomolies genetiques

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Problems: style and meaning

English• Two sentences• infectious disease was no

longer much of a threat in the developed world

• The remaining challenges to public health there

• noninfectious conditions

French• One sentence• les pays industrialises

etait debarasses des risques lies aux maladies infectieuses

• la sante publique n’etait menacee que

• maladies

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Translation

• These tasks are extremely difficult.

• They are more than what we expect of a human translator, let alone a computer.

• The work of human translators is typically multi-stage.

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Translation Workflow

Pre-editing

Post-editing

Translation

LANGUAGERESOURCES

??

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Translation Workflow

Pre-editing

Post-editing

Translation

LANGUAGERESOURCES

dictionariesgrammarsterminologyexistingtranslations

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Translation Workflow

• No pre-editing Lots of post-editing!• Lots of pre-editing Less post-editing!• GARBAGE IN, GARBAGE OUT!!!

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Translation Workflow: Pre-editing

• Text Preparation– Delimitation of what is to be translated– Representation in electronic form– Spelling correction

• Stylistic guidelines, e.g. – avoidance of long sentences– avoidance of ambiguous terms

• Use of controlled languages and related tools– Grammar Checkers – Critiquing Systems

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Translation Workflow

• Coordination of a large translation job– Distribution of task to several translators– Integration of results– Communication of between translators and

cooordinator

• Availability of language resources– Grammar– Dictionaries– Terminology– Existing translations

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Controlled Languages• Average number of words used by native speaker –

75,000. • Basic English, invented by Ogden (1930). Vocabulary

size 850.• Simplified constructions e.g. ``make perfect'' instead of

``perfect''. – Learn English – seven years– Learn Esperanto – seven months– Learn BE – seven weeks

• Some industries have introduced controlled languages for their manuals.

• Xerox offers its technical writers one-day course, British Aerospace does the same in a few short sessions

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Translational Equivalence

• Lexical Mismatches

• Cultural Mismatches

• Grammatical/Structural Mismatches

• Structural/Semantic Mismatches

• Role of Context

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Lexical Mismatches

English• ?• spam• friend• truck• lorry• just

French• Alpe• ?• ami• amie• camion• venir de

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Words with Many Senses

Hutchins & Somers (1992)

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Cultural Mismatches

English: Health InsuranceFrench: Assurance Maladie

English:validateFrench: oblitérer

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Cultural Mismatches

It's no good closing the barn door afterthe horse has bolted

Moutarde après le dîner

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Grammatical/Structural Mismatches

• I miss you• I like sausages

• tu me manques• Ich habe wursten

gern

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Structural/Semantic Mismatches

• Head marking.– In English possessive relation is marked on

the owner: The man's house– In Hungarian it is marked on the dependent:

The man house-his– his house / sa maison

• Direction and manner of motion marking– He ran into the room (English)– He entered the room running (French)

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Contextual Interpretation

OPEN

OPEN

ouvert ouvre

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Structural Ambiguity

• I forgot how good beer tastes

• Time flies like an arrow

• I bought a car with four doors/liri

• The councillors refused the women a permit because they advocated/feared violence.

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Similarities and Differences Between Languages

Differences• Lexical Marking of

semantic distinctions• Morphology

– English– Maltese– German

• Word order

Similarities• Communicative

function for survival• Mechanisms for

reference to people, eating, politeness, time.

• Nouns• Verbs

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Morphology

• try, tries, tried, trying

• nikteb, tikteb, jikteb, jiktebt, niktbu,...

• uygarlastiramadimizdanmisiklarsinizcasma

• behaving as if you are amongst those whom we could not cause to become civilized

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Differences in Word Order

• SVO (English)The man kicked the ball

• SOV (Japanese)The man the ball kicked

• VSO (Classical Arabic)Kicked the man the ball

• Mixed (German)The man who the sausage ate did.

• Free word order (Latin)

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Summary

• Translation concerns translational equivence• This transcends equivalence of meaning (e.g.

sometimes involves cultural conventions)• Translation may involve the resolution of

ambiguity.• It makes sense to talk about the distance

between languages. Languages which are close are easier to translate.

• Translation is a hard problem – for humans let alone machines.

Why Machine Translation is Important

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Implications of Multilinguality

Number of Languages

Number of Language

Pairs

2 2

3 6

10 90

20 380

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Commerical Interest

• US has invested in MT for intelligence purposes

• MT is popular on the web - the most ued of Google's special features

• EU spends more that €1B per annum on translation

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Academic Interest

• Different NL technologies include– parsing– generation– morphology– pronoun resolution– understanding ...

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Misconceptions about MT

• MT is a waste of time because– you will never make a machine that can

translate Shakespeare. – the quality  of translation you can get from an

MT system is very low• MT threatens the jobs of translators. • MT systems are machines, and buying an

MT system should be very much like buying a car.

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Facts about MT• There are many situations where the ability to

produce reliable, if less than perfect, translations at high speed is valuable.

• MT systems can take over some of the boring, repetitive translation jobs and allow human translation to concentrate on more interesting specialist tasks.

• Building an MT system is an arduous and time consuming job, involving the construction of grammars and very large monolingual and bilingual dictionaries.

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The Place for MT• Human Translators are good at:

– Getting the right turn of phrase– Preserving translation equivalence

• Human Translators are bad at– Dictionary look-up – Consistency of translation – Translation of terminology

• MT can exploit these weaknesses

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Summary

MT is important because – There are too few human translators– Availability of materials in appropriate

language has significant economic consequences.

– Scientifically, it is still one of the best test areas for language technology

Machine Translation and Human Translators

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Different Styles of MT

• FAMT: fully automatic machine translation– FAHQMT– FALQMT

• MAHT: machine aided human translation

• HAMT: human aided machine translation

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The Dream of FAMT

• Fully Automatic (High Quality) Machine Translation (Bar Hillel 1960)

Source Language

text

TargetLanguage

text

FAHQMT

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FAMT

• Basic Charactistics– No human intervention– Arbitrary text

• Evaluation Criteria– Quality of ouput– Cost ($/page)– Speed (pages/hour)

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FAMT Success StoryTAUM METEO

• Written by Chevalier et al. 1978.• Translation of weather reports from

English to French• Highly constrained subset of English:

– Small number of senses for each word– Restricted syntactic constructions

• System determines whether a given sentence is within its capabilities

• Very fast, very accurate, no post-editing

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FAMT: MORAL

• FAMT can work well but only if we give up one or more of the goals e.g.– Unrestricted text input– High quality translation

• This observation has lead to research on sublanguages

• And to the use of FALQT

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Sublanguages

• Restricted domain of reference

• Restricted purpose and orientation

• Restricted mode of communication (may include bandwidth considerations)

• Community of users sharing specialised knowledge

• Examples: Weather reports; financial reports; car accident reports

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Stock Market Report (ToM)

• Back to the Malta Stock Exchange: it was a positive week with gainers outpacing losers 6-3, and large cap stocks regaining popularity. Equity turnover by value topped the Lm600,000 mark by a comfortable margin for the second time this year and the MSE index closed the week at 5,123.766, up 1.5%.BoV opened the week flat at Lm3.651 but advanced steadily on sustained buying activity to close at Lm3.68. The positive mood extended into Tuesday as the price climbed further, closing at Lm3.70.

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Fully Automatic Low Quality Translation – (FALQT)

• Can be used where translation volume is high.

• Where the gist is more important than an accurate translation

• Where we need to select a small group of documents from a large collection for subsequent high quality translation.

• Must answer question: could document X in collection Z be about Y?

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Google Translation

• En 2000-01, le recouvrement des couts mettra l'emphase sur la reduction des comptes a recevoir et la mise en place d'un programme de verification aupres des firmes ayant demande une reduction des frais. En 2000-01, le budget du programme devrait augmenter substantiellement du a des nouvelles initiatives du cote appropriation.

• In 2000-01, the covering of the costs will put the emphase on the reduction of the accounts receivable and the installation of a programme of checking near the firms having required a reduction of the expenses. In 2000-01, the budget of the program should increase substantially due to new initiatives on the side appropriation.

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FAMT is not the only way

• FAMT lies at one extreme of a continuum of ways in which technology can be brought to bear upon the translation problem

• At the other extreme there are word processing software, fax machines, and even mobile phones

• Between these two extremes there are other points of interest where technology can radically affect the productivity of the individual translator.

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MAHT and HAMT

• Machine Aided Human Translation (MAHT)

• Human Aided Machine Translation (HAMT).

• The essential difference between these two lies not only in the way in which the person is involved but also in the extent of their involvement

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MAHT

• All initiative resides with the human.• Often based on a text editor with certain

translation-specific functionalities such as– Simultaneous access to source and target texts– Online access to dictionaries, thesauri, terminological

databases, and word concordance tools.

• Identification of and access to secondary materials such as texts being worked on and other texts like it in both source and target forms.

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MAHT - Translation Memories

• Systems consist of a database in which each source sentence of a translation is stored together with the target sentence (this is called a translation memory "unit")

• Any new source sentences will be searched for in the database and a match value is calculated.

• When the match value is 100%, the translation of the source sentence from the database is inserted into the text being translated.

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MAHT - Translation Memories

• If the match value is below 100% and above a certain user-definable percentage (i.e., "fuzzy match"), the old translation will be inserted as a translation proposal for the translator to review and edit.

• Sentences with match values below that margin have to be translated from scratch.

• New and changed translation proposals will then be stored in the database for future use.

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MAHT - Translation Memories – Advantages

• Avoid redoing translation of repeated material

• Use previous texts as a model for new translations

• Ensure consistency throughout a translation

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MAHT - Translation Memories - Drawbacks

• If terminology changes between projects the content of a TM needs to be updated to reflect these changes.

• Blind faith in exact matches (without validation) can generate incorrect translation since typically there is no verification of context.

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MAHT - Translation Memories - Remarks

• Translation Process: TM tools may not easily fit into existing translation or localization processes: work best where work can be signed off in pieces rather than as a whole.

• Customisation: rarely works straight out of the box. Menu adaptation, filters to desktop applications may require significant effort.

• Investment costs are high and must include setup and maintenance of TMs.

• OpenTag/TMX formats for exchanging TM data between competing systems

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MAHT – Other Technology

• Communication/coordination amongst translators

• Integration of internet technologies and web services.

• Database technology, smart indexing, and networking

• Improvements can be achieved that are well within the scope of current technology.

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HAMT – Human Assisted Machine Translation

• Machine retains the initiative but works in collaboration with human consultant.

• System translates autonomously until it recognises that a linguistic difficulty of a certain type has arisen, e.g.– ambiguity– pronoun reference– unknown word– unrecognised construction

• At this point it seeks help from the consultant.

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HAMT – Challenges

• Reliable identification/classification of difficulty.

• Reliable communication of difficulty to user.

• Tradeoff between quality and scope of translation.

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HAMT - Advantages

• Modulo challenges – a high quality of translation can be guaranteed.

• Speed – if large sections of text can be translated automatically.

• Human consultant need not necessarily have all the skills of a human translator; native competence in one or both languages may suffice.

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Summary

• Machine Translation is a continuum– FAMT– HAMT– MAHT

• The utility of a given type of system cannot be assessed with very simple criteria

• Utlility function involves at least the human cost, the machine cost, the quality of the result, and the nature of the translation requirements.