Simultaneous Consecutive Interpreting: A New Technique Put to the Test
Bibliographic record
Abstract
The paper reports a small-scale experimental study to test the viability or even superiority of technology-assisted consecutive interpreting as a new working method for conference interpreters. In this technique, pioneered in 1999 by an EU staff interpreter, a digital voice recorder is used to record the original speech which the interpreter then plays back into earphones and renders in the simultaneous mode. The performances of three experienced professional interpreters (French-German) in the conventional consecutive and the ‘simultaneous consecutive’ mode were assessed and compared on the basis of transcript analysis, self-assessment and audience response. Our findings suggest that simultaneous consecutive permits enhanced interpreting performances, as reflected in more fluent delivery, closer source–target correspondence, and fewer prosodic deviations. Though the interpreters’ personal working experience and preferences appeared to have a significant influence on their performance, all three subjects easily adopted the technology-assisted interpreting mode and considered it a viable technique.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".