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Evaluating Sight Translation: A Corpus-based Approach

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Title: Evaluating Sight Translation: A Corpus-based Approach


1
Evaluating Sight Translation A Corpus-based
Approach
  • Wallace Chen, PhD
  • Assistant Professor
  • Graduate School of Translation, Interpretation,
    and Language Education (GSTILE)
  • Monterey Institute of International Studies
  • Monterey, California, USA
  • wallace.chen_at_miis.edu

2
Outline
  • Sight Translation
  • Current assessment approach
  • Corpus-based assessment approach
  • Data
  • Applications findings
  • Implications conclusions

3
Sight Translation
  • an integral part of 1st-year translation courses
  • skim a text and verbally translate at the same
    time
  • Skills required
  • analytical skills
  • cohesion / transition
  • vocabulary
  • time management
  • summarizing skills
  • pressure / stress management

4
Current assessment approach
  • assess performance based on verbal output
  • length of text less than 1,000 words
  • assessment criteria
  • meaning (accuracy), completeness, naturalness,
  • backtracking, pauses, time management,
  • grammar, pronunciation, numbers, terminology,
  • register, cohesion/coherence, sentence
    structure
  • Class review and introspection

5
Corpus-based assessment approach
  • Corpus a systematic collection of texts on
    computer for purposes of linguistic research
  • quantitative analysis in support of qualitative
    introspection
  • reference (parallel) texts for improving
    translation quality
  • data retrieval for the analysis of translation
    behaviors

6
Data
  • Reference Corpus (RC) 28,000 words
  • Subjects rainforest conservation, computing,
    telecommunications
  • Translation Learners Corpus (TLC)
  • - 2 sight translation exams (1 with reference
    official translation)
  • - 32 students
  • - 64 transcripts of sight translation into
    English
  • Corpus of Comment Tags (CCT)
  • - 10 texts with comment tags

7
Three corpora applications and findings (I)
  • Reference Corpus (RC)
  • - collocation
  • - terminology
  • - idiomatic expressions
  • - confirmation of intuition
  • - translation equivalent
  • - target language patterns
  • - new expressions some examples

8
Three corpora applications and findings (II)
  • Translation Learners Corpus (TLC)
  • - compare translation behaviors among students
  • - compare between student translation and
    reference translation
  • - time management students finishing earlier
    have a tendency to score higher
  • - lengthy translations suggest lexical overuse
    (39 vs. 59 for and)

9
Three corpora applications and findings (III)
  • Corpus of Comment Tags (CCT)
  • - fewer tags mean higher scores
  • - fast translators receive fewer tags
  • - repeated tags suggest common textual
    difficulties
  • - comment tags reveal room for improvement for
    individual translators

10
Implications conclusions
  • Supplement current approaches to assessment
  • Identify and visualize common issues
  • Understand translation patterns and suggest room
    for being flexible
  • Learn from examples
  • Corpus construction for research and teaching
    purposes, e.g. text selection
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