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Data-Driven Machine Translation for Sign Languages

Data-Driven Machine Translation for Sign Languages. Sara Morrissey PhD topic NCLT/CNGL Workshop 23 rd July 2008. outline. background main problems data-driven MT for SLs experiments and results conclusions. background. communication interpreters and technological aids

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Data-Driven Machine Translation for Sign Languages

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  1. Data-Driven Machine Translation for Sign Languages Sara Morrissey PhD topic NCLT/CNGL Workshop 23rd July 2008

  2. outline • background • main problems • data-driven MT for SLs • experiments and results • conclusions

  3. background • communication • interpreters and technological aids • machine translation • automatic and confidential • native language of users • rule-based approaches (Veale et al., 1998, Marshall & Sáfár, 2002) • data-driven approaches • Bauer et al., 1999, Stein et al., 2006, Wu et al., 2007

  4. main problems • representation no formally adopted writing system • linguistic analysis little research • appropriate data difficult to find • evaluation visual-spatial nature rules out automatic

  5. data-driven MT for SLs • initial prototype system using Dutch SL • MaTrEx system • Air Traffic Information System (ATIS) Corpus • 595 English sentences • multi-lingual – ISL parallel corpus creation • manual annotation with semantic glosses

  6. data representation (Early morning flights between Cork and Belfast) EARLY MORNING BETWEEN be-CORK CORK FLY BELFAST BETWEEN ref-BELFAST ref-CORK

  7. MATREX: data-driven machine translation English  ISL •  bilingual database

  8. translation directions Spoken Language Text  SL Recognition SL Generation SL Annotation

  9. experiments and results • machine translation experiments • 2 segmentation methodologies • type 1 chunks uses Marker Hypothesis (Green, 1979) • type 2 uses dual segmentation method • Early morning flights between Cork and Belfast • <ADJ> early morning flights <PREP> between Cork <CONJ> and Belfast

  10. experiments and results

  11. animation • real human signing preferred (Naqvi, 2007) but impractical • avatar animation • criteria: realistic, consistent, functional, fluid • Poser Animation Software Version 6.0 • 50 randomly selected sentences, 66 hand-crafted videos • problem of fluidity

  12. animation ‘or’ how much ‘e’ flight http://www.computing.dcu.ie/~smorri/ISL_AnimationDemo.html

  13. experiments and results • human evaluation experiments • 4 native Deaf human monitors • web-based evaluation of 50 ISL translations • evaluated intelligibility and fidelity • 82% animations = intelligible • 72% animations = good-excellent translations • HCI analysis using Nielsen’s approach

  14. conclusion • MT methodology never before applied to SLs • multi-component system, bidirectional system • practical, technological alternative to help alleviate communication and comprehension for Deaf community • positive automatic and manual evaluation • scope for incorporating different SL representation methodologies and segmentation techniques

  15. thank you questions? smorri@computing.dcu.ie

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