Coping with Surprise: Multiple CMU MT Approaches

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Coping with SurpriseMultiple CMU MT Approaches

• Alon Lavie
• Lori Levin, Jaime Carbonell,
• Alex Waibel, Stephan Vogel,
• Ralf Brown, Robert Frederking
• Language Technologies Institute
• Carnegie Mellon University
• Joint work with
• Katharina Probst, Erik Peterson, Joy Zhang,
• Fei Huang, Alicia Tribble, Ariadna Font-Llitjos,
• Rachel Reynolds, Richard Cohen

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Main Hindi SLE Efforts

• Data Collection
• Elicited Data Collection
• Data from contacts in India
• Web Crawling
• Language Processing Utilities
• Morphology
• Encoding identification and conversion
• MT system development
• XFER system
• SMT system
• EBMT system

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Elicited Data Collection

• Goal Acquire high quality word aligned
  Hindi-English data to support XFER system
  development (grammar learning)
• Recruited team of 20 bilingual speakers at CMU
  and in India
• Extracted a corpus of phrases (NPs and PPs) from
  Brown Corpus section of Penn TreeBank
• Controlled Elicitation Corpus (typologically
  diverse, limited vocabulary) also translated into
  Hindi
• Resulting in total of 17589 word aligned
  translated phrases (50KB)

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The CMU Elicitation Tool
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Elicited Data Collection

• Problems and issues
• English ? Hindi direction allowed us to use the
  Penn TreeBank to extract accurate phrases
• However, bilingual informants not accustomed to
  type Hindi ? typos
• Limits utility of the data, less effect on
  accuracy
• Using the WSJ portion of the PennTB may have been
  a better fit for genre

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Main CMU Contributions to SLE Shared Resources

• Elicited Data Corpus (50KB)
• Indian Government Parallel Text ERDC.tgz (338 MB)
• CMU Phrase Lexicon Joyphrase.gz (3.5 MB)
• Cleaned IBM lexicon ibmlex-cleaned.txt.gz (1.5
  MB)
• CMU Aligned Sentences CMU-aligned-sentences.tar.gz
  (1.3 MB)
• CMU Phrases and sentences CMU-phrasessentences.zi
  p (468 KB)
• Bilingual Named Entity List IndiaTodayLPNETranslis
  ts.tar.gz (54KB)
• Web Crawling
• Most sites with possible parallel texts had Hindi
  in proprietary encodings
• Osho http//www.osho.com/Content.cfm?LanguageHin
  di

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Hindi Morphological Analyzer

• http//www.iiit.net/ltrc/morph/index.htm
• High quality and high coverage morphological
  analyzer from IIIT
• Input full inflected forms (RomanWX encoding)
• Output root form collection of features
• Installing as a local server required some
  effort, e.g. UTF-8 ? RomanWX
• Used primarily in our XFER system

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Other Hindi Processing Utilities

• Encoding identification and conversion tools
• Built two automatic encoding identifiers, used
  for web data collection
• Located and installed encoding converters from a
  variety of encodings
• Most widely used was UTF-8 to RomanWX

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XFER System for Hindi

• Three passes
• match against phrase-to-phrase entries
  (full-forms, no morphology)
• morphologically analyze input words and match
  against lexicon
• matches feed into manual and learned transfer
  rules
• match original word against lexicon - provides
  word-to-word translation as fall-back for input
  not otherwise covered
• Simple decoding greedy left-to-right search that
  prefers longer input segments NIST 5.35
• Strong decoding with latticesLM NIST 5.47

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Examples of Learned Rules
NP,14244 Score0.0429 NPNP N -gt DET N ( (X1Y2) )
NP,14434 Score0.0040 NPNP ADJ CONJ ADJ N -gt ADJ CONJ ADJ N ( (X1Y1) (X2Y2) (X3Y3) (X4Y4) )
PP,4894Score0.0470PPPP NP POSTP -gt PREP NP((X2Y1)(X1Y2))
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SMT System for Hindi

• Resources
• Trained on commonly available bilingual corpora
• Used bilingual Hindi-English dictionary
• Named Entities
• 70 million word English LM
• CMU SMT System
• Tuned on ISI devtest data
• Monotone decoding, as reordering did not result
  in improvement on this test set
• Mixed casing based on Named Entities and simple
  rules
• NIST score 6.74

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EBMT System for Hindi

• Training data same as SMT a few hand-written
  equivalent class generalizations
• English LM built from APW portion of GigaWord
  Corpus (600M words)
• Encoding variation raw training data in a
  variety of different encodings ? all converted to
  UTF-8 (already supported by EBMT)
• Preprocessing of example phrases to improve word
  matching
• Match Hindi possessive with English s
• NIST Score 5.98

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A Truly Limited Data Scenario for Hindi-to-English

• Put together a scenario with very miserly data
  resources
• Elicited Data corpus 17589 phrases
• Cleaned portion (top 12) of LDC dictionary
  2725 Hindi words (23612 translation pairs)
• Manually acquired resources during the SLE
• 500 manual bigram translations
• 72 manually written phrase transfer rules
• 105 manually written postposition rules
• 48 manually written time expression rules
• No additional parallel text!!
• Results presented tomorrow

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Other CMU Contributions to SLE Shared Resources

• FOUND RESOURCES not on LDC Website
• From TidesSLList Archive website
• Vogel email 6/2
• Hindi Language Resources http//www.cs.colostate.
  edu/malaiya/hindilinks.html
• General Information on Hindi Script
  http//www.latrobe.edu.au/indiangallery/devanagari
  .htm
• Dictionaries at http//www.iiit.net/ltrc/Dictiona
  ries/Dict_Frame.html
• English to Hindu dictionary in different formats
  http//sanskrit.gde.to/hindi/
• A small English to Urdu dictionary
  http//www.cs.wisc.edu/navin/india/urdu.dictionar
  y
• The Bible at http//www.gospelcom.net/ibs/bibles/
  
• The Emille Project http//www.emille.lancs.ac.uk/
  home.htm
• Hardcopy phrasebook references
• A Monthly Newsletter of Vigyan Prasar
• http//www.vigyanprasar.com/dream/index.asp
• Morphological Analyser http//www.iiit.net/ltrc/m
  orph/index.htm

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Other CMU Contributions to SLE Shared Resources

• FOUND RESOURCES not on LDC Website (cont.)
• From TidesSLList Archive website
• Tribble email, via Vogel 6/2 Possible parallel
  websites
• http//www.bbc.co.uk (English)
• http//www.bbc.co.uk/urdu/ (Hindi)
• http//sify.com/news_info/news/
• http//sify.com/hindi/
• http//in.rediff.com/index.html (English)
• http//www.rediff.com/hindi/index.html (Hindi)
• http//www.indiatoday.com/itoday/index.html
• http//www.indiatodayhindi.com
• Vogel email 6/2
• http//us.rediff.com/index.html
• http//www.rediff.com/hindi/index.html Already
  listed
• http//www.niharonline.com/
• http//www.niharonline.com/hindi/index.html
• http//www.boloji.com/hindi/index.html
• http//www.boloji.com/hindi/hindi/index.htm
• The Gita Supersite http//www.gitasupersite.iitk.a
  c.in/

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Other CMU Contributions to SLE Shared Resources

• FOUND RESOURCES not on LDC Website (cont.)
• From TidesSLList Archive website
• 6/20 Parallel Hindi/English webpages
• GAIL (Natural Gas Co.) http//gail.nic.in/
  UTF-8. Found by CMU undergrad Web team Mike
  Maxwell, LDC, found it at the same time.
• SHARED PROCESSED RESOURCES NOT ON LDC WEBSITE
• From TidesSLList Archive website
• Frederking email 6/3 announced, 6/4 provided
• Ralf Brown's idenc encoding classifier
• Frederking email 6/5
• PDF extractions from LanguageWeaver URLs
  http//progress.is.cs.cmu.edu/surprise/Hindi/ParDo
  c/06-04-2003/English/ http//progress.is.cs.cmu.ed
  u/surprise/Hindi/ParDoc/06-04-2003/Hindi/
• Frederking email 6/5
• Richard Wang's Perl ident.pl encoding classifier
  and ISCII-UTF8.pl converter
• Frederking email 6/11
• Erik Peterson here has put together a Perl
  wrapper for the IIIT Morphology package, so that
  the input can be UTF-8 http//progress.is.cs.cmu.
  edu/surprise/morph_wrapper.tar.gz

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Other CMU Contributions to SLE Shared Resources

• SHARED PROCESSED RESOURCES NOT ON LDC WEBSITE
  (cont.)
• From TidesSLList Archive website
• Levin email 6/13
• Directory of Elicited Word-Aligned English-Hindi
  Translated Phrases http//progress.is.cs.cmu.edu/
  surprise/Elicited-Data/
• Frederking email 6/20
• Undecoded but believed to be parallel webpages
  http//progress.is.cs.cmu.edu/surprise/merged_urls
  .txt
• PDF extractions from same http//progress.is.cs.c
  mu.edu/surprise/merged_urls/
• Frederking email 6/24
• Several individual parallel webpages sites may
  have more www.commerce.nic.in/setup.htm www.comme
  rce.nic.in/hindi/setup.html mohfw.nic.in/kk/95/boo
  ks1.htm mohfw.nic.in/oph.htm wwww.mp.nic.in