CSA405: Advanced Topics in NLP

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CSA405 Advanced Topicsin NLP

• Machine Translation I
• Introduction to MT

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Outline

• MT Machine Translation
• Why MT is important
• What MT is and why MT is difficult
• MT and the Human Translator

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Why Machine Translation is Important
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Misconceptions about MT

• There was/is an MT system which translated The
  spirit is willing, but the flesh is weak into the
  Russian equivalent of The vodka is good, but the
  steak is lousy, and hydraulic ram into the French
  equivalent of water goat. MT is useless.
• MT is a waste of time because you will never make
  a machine that can translate Shakespeare.
• Generally, the quality  of translation you can
  get from an MT system is very low. This makes
  them useless in practice.
• MT threatens the jobs of translators.
• The Japanese have developed a system that you can
  talk to on the phone. It translates what you say
  into Japanese, and translates the other speaker's
  replies into English.
• There is an amazing South American Indian
  language with a structure of such logical
  perfection that it solves the problem of
  designing MT systems.
• MT systems are machines, and buying an MT system
  should be very much like buying a car.

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Some Facts about MT

• MT is useful. The METEO  system has been in daily
  use since 1977. As of 1990, it was regularly
  translating around 45 000 words daily. In the
  1980s. It also produces high quality output.
• While MT systems sometimes produce howlers, there
  are many situations where the ability of MT
  systems to produce reliable, if less than
  perfect, translations at high speed is valuable.
• MT does not threaten translators' jobs. The
  limitations of current MT systems are too great.
  However, MT systems can take over some of the
  boring, repetitive translation jobs and allow
  human translation to concentrate on more
  interesting specialist tasks.
• Speech-to-Speech MT is still a research topic.
  Verbmobil has been developed in Germany.
• Building an MT system is an arduous and time
  consuming job, involving the construction of
  grammars and very large monolingual and bilingual
  dictionaries. There is no magic solution' to
  this.
• Before an MT system becomes really useful, a
  user will typically have to invest a considerable
  amount of effort in customization.

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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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Implications of Multilinguality
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MT is important because...

• There are too few human translators
• Socio-political considerations require it.
• Availability of materials in appropriate language
  has significant economic consequences.
• Scientifically, it is still one of the best test
  areas for language technology
• Philosophically, it demands practical solutions
  to old problems (e.g. role of knowledge and
  understanding in translation).negatively charged
  electrons and protons

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How much is MT used?

• It is a myth that MT is not used
• In 2000, MT specialist Scott Bennett said
  Altavista's BabelFish ... initiated 1997, is now
  used a million times per day.
• In 2001, Softissimo announced that the Internet
  translation request volume processed by
  www.reverso.net has now reached several million
  (Web pages, e-mail, short texts and results of
  search engine requests) per month on its mail
  translation portal and the portals of its
  Internet partners.
• V.d. Meer (2003) "Every day, portals like
  Altavista and Google process nearly 10 million
  requests for automatic translation.
• MT usage is increasing

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How much more could it be used?

• Translation/localisation industry has so far
  focused largely on product documentation
• This represents less than 20 of all text-based
  information repositories that need to be
  localised
• ?Corporate decision makers and governments will
  have to begin supporting multilingual
  communication initiatives and strategies.

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Why Translation is Difficult
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What is Translation?

• The process of transforming text from one
  language into another language.
• A written communication in a second language
  having the same meaning as the written
  communication in a first language
• It is what translators actually do! (Martin Kay)
  

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What Translators Actually DoAn Example of En/Fr
Translation

• As 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 dannees, on croyait que les
  pays industrialises etait debarasses des risques
  lies aux maladies infectieuses et que la sante
  publique netait 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 netait menacee que
• maladies

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Problems Contextual Interpretation
OPEN
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Problems Non-Equivalences, Lexical Gaps

• English
• Room
• I arrive/am arriving
• ?Consumptions?
• VAT
• ?bits and pieces?
• I miss you

• French
• Salle/chambre/piece
• Jarrive
• Consommations
• TVA
• Petites fournitures
• Tu me manques

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Cultural Models
English Health Insurance German Krankenversiche
rung French Assurance Maladie
English stamp German entwerten French
obliterer
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Structural Ambiguity

• I bought a car with four doors/liri
• I forgot how good beer tastes
• Time flies like an arrow
• The councillors refused the women a permit
  because they advocated/feared violence.

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Summary

• Translation is about more than equivalence of
  meaning.
• Translation may involve the resolution of
  ambiguity.
• Preservation of intention involves cultural
  background as well as linguistic knowledge.
• Translation is a hard problem for humans let
  alone machines.

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Similarities and Differences Between Languages

• Differences
• Morphology
• Word order and syntactic structures
• Marking of semantic distinctions
• Lexical

• Similarities
• Communicative function for survival
• Mechanisms for reference to people, eating,
  politeness, time.
• Syntactic complexity
• Nouns
• Verbs

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Differences in Morphology

• Number of morphemes per word
• One morpheme per word (Vietnamese)
• Many morphemes per word (Maltese)
• Segmentability of morphemes
• Agglutinative (Turkish)uygarlastiramadiklar
  imizdanmis sinizcasinabehaving as if you are
  among those whom we could not case to become
  civilised.
• Fusion single affix multiple morphemes
  (Russian)
• stolom with (a) table(om SING/INSTR/DECL1)

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Differences in Word Order

• SVO (English)The man kicked the ball
• SOV (Japanese)The man the ball kicked
• Mixed (German)The man (has) the ball kicked must
  
• VSO (Classical Arabic)Kicked the man the ball
• Free word order (Latin)

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Differences in Marking of Semantic Information

• Head marking.
• In English possessive relation is marked on the
  head The man's house
• In Hungarian it is marked on the dependentThe
  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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Lexical DifferencesSemantic Granularity
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Hutchins Somers (1992)
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Lexical Differences

• Lexical gaps when a word exists in one language
  but not in another
• Japanese does not have a word corresponding to
  privacy.
• English does not have a word for Japanese oyakoko
  ( filial piety).
• Sapir/Wharf hypothesis
• Language constrains thought
• Speakers of different languages employ different
  conceptual systems
• Impossibility of translation in general.

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Machine Translation and Human Translators
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In the Beginning ....was 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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Translation Process 1

• Pre-editing
• Translation
• Post-editing
• No pre-editing ? Lots of post-editing!
• Lots of pre-editing ? No(t much) post-editing!
• GARBAGE IN, GARBAGE OUT!!!

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Pre-editing

• What constitutes Good Input?
• Depends on system.
• short, simple, grammatical sentences
• New toner units are held level during
  installation and, since they do not as supplied
  contain toner, must be filled prior to
  installation from a small cartridge.
• Fill the new toner unit with toner from a toner
  cartridge. Hold the new toner unit level while
  you put it in the printer.

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Pre-editing

• Avoidance of ambiguous terms
• Trend towards controlled languages and related
  tools
• Spellcheckers
• Grammar Checkers
• Critiquing Systems
• Controlled English to make English accessible and
  useable by greatest no. of people. Basic English,
  cf Esperanto.
• Main idea to reduce no. of general words needed
  for writing anything to a few hundred from 75000
  (avg. for skilled native speakers) by operator
  verbs, e.g. make perfect'' instead of
  perfect''.
• Xerox offers its technical writers one-day
  course, British Aerospace does the same in a few
  short sessions

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Translation Process 2

• Coordination
• Communication
• In theory, FAMT is meant to usurp pre-editing,
  translation, post-editing phases.
• But even with current technology, no system can
  be built which satisfies all of FAMT's goals
  simultaneously

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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
  sub-languages
• 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
• See Kittredge (1985) for further details of what
  computational techniques are applicable to
  sublanguages

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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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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 there is
  no verification of the context where the new
  segment is used compared to where the original
  one was used.

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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
• Setup and maintenance of TMs has to factored in.
• 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.

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Some References

• Jonathan Slocum, Machine Translation its
  History, Current Status, and Future Prospects,
  Proc ACL 1984, Stanford University,
  http//acl.ldc.upenn.edu/P/P84/P84-1116.pdf
• Martin Kay Machine Translation, Computational
  Linguistics vol 11 numbers 2-3 1985.
• Richard Kittredge Sublanguages, Computational
  Linguistics vol 11 numbers 2-3 1985.