• Corpus ID: 21675165

Overview of the IWSLT 2017 Evaluation Campaign

@inproceedings{Cettolo2017OverviewOT,
  title={Overview of the IWSLT 2017 Evaluation Campaign},
  author={Mauro Cettolo and Marcello Federico and Luisa Bentivogli and Niehues Jan and St{\"u}ker Sebastian and Sudoh Katsuitho and Yoshino Koichiro and Federmann Christian},
  booktitle={International Workshop on Spoken Language Translation},
  year={2017}
}
The IWSLT 2017 evaluation campaign has organised three tasks. The Multilingual task, which is about training machine translation systems handling many-to-many language directions, including so-called zero-shot directions. The Dialogue task, which calls for the integration of context information in machine translation, in order to resolve anaphoric references that typically occur in human-human dialogue turns. And, finally, the Lecture task, which offers the challenge of automatically… 

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References

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The IWSLT 2016 Evaluation Campaign featured two tasks: the translation of talks and thetranslation of video conference conversations, which showed improvements over the best submissions of last year.

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The IWSLT 2015 Evaluation Campaign featured three tracks: automatic speech recognition (ASR), spoken language translation (SLT), and machine translation (MT), which involved the transcription or translation of TED talks, either made available by the official TED website or by other TEDx events.

FBK’s Multilingual Neural Machine Translation System for IWSLT 2017

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The NMT model was able to translate between these language pairs and the translations were either as good as or better than the non zero resource setting, and the NMT models that use feed forward layers and self attention instead of recurrent layers are extremely fast in terms of training.

KIT’s Multilingual Neural Machine Translation systems for IWSLT 2017

KIT’s multilingual neural machine translation systems for the IWSLT 2017 evaluation campaign machine translation (MT) and spoken language translation (SLT) tasks are presented and an effective adaptation scheme for multilingual systems is suggested which brings great improvements compared to monolingual systems.

Overview of the IWSLT 2012 evaluation campaign

The ninth evaluation campaign organized by the IWSLT workshop offered multiple tracks on lecture translation based on the TED corpus, and one track on dialog translation from Chinese to Englishbased on the Olympic trilingual corpus.

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GTCOM’s neural machine translation(NMT) systems for the International Workshop on Spoken Language Translation(IWSLT) 2017 are described and two deep architectures, layer nomalization, weight normalization and training models with annealing Adam are explored.

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The statistical machine translation systems of RWTH Aachen University developed for the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2011 are presented and can show considerable improvements over the respective baseline systems.

Complexity of spoken versus written language for machine translation

This paper analyzes two popular genres: spoken language and written news, using publicly available corpora which stem from the popular WMT and IWSLT evaluation campaigns, and shows that there is a sufficient amount of difference between the two genres.