Papers by Stephan Vogel

2 papers
The WAW Corpus: The First Corpus of Interpreted Speeches and their Translations for English and Arabic (L18-1)

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Challenge: Using the corpus, we study the characteristics of interpreters' work and train machine translation systems.
Approach: They propose to build an interpreting corpus for Arabic and an Arabic corpus to study interpreters' work.
Outcome: The proposed corpus can be used for teaching interpreters and to train machine translation systems.
Incremental Decoding and Training Methods for Simultaneous Translation in Neural Machine Translation (N18-2)

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Challenge: a tunable agent decides the best segmentation strategy for a user-defined BLEU loss and Average Proportion (AP) constraint.
Approach: They propose a tunable agent which decides the best segmentation strategy for a user-defined BLEU loss and average proportion (AP) constraint.
Outcome: The proposed agent outperforms existing Wait-if-diff and Wait-If-worse agents on BLEU with a lower latency.

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