Evaluating productivity gains of hybrid ASR-MT systems for translation dictation

  title={Evaluating productivity gains of hybrid ASR-MT systems for translation dictation},
  author={Alain D{\'e}silets and Marta Stojanovic and Jean-François Lapointe and Rick Rose and Aarthi M. Reddy},
This paper is about Translation Dictation with ASR, that is, the use of Automatic Speech Recognition (ASR) by human translators, in order to dictate translations. We are particularly interested in the productivity gains that this could provide over conventional keyboard input, and ways in which such gains might be increased through a combination of ASR and Statistical Machine Translation (SMT). In this hybrid technology, the source language text is presented to both the human translator and a… CONTINUE READING

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Key Quantitative Results

  • We found that the ASR system had an average Word Error Rate (WER) of 11.7%, and that translation using this system did not provide statistically significant productivity increases over keyboard input, when following the manufacturer recommended procedure for error correction.
  • But text entry only about half the work, which also includes: • Pre-reading • Terminology and phraseology searches • Self-revision • Gain for the whole end-to-end translation task might be closer to 20%.

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