English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper describes FBK's submission to the end-to-end English-German speechtranslation task at IWSLT 2018. Our system relies on a state-of-the-art modelbased on LSTMs and CNNs, where the CNNs are used to reduce the temporaldimension of the audio input, which is in general much higher than machinetranslation input. Our model was trained only on the audio-to-text paralleldata released for the task, and fine-tuned on cleaned subsets of the originaltraining corpus. The addition of weight normalization and label smoothingimproved the baseline system by 1.0 BLEU point on our validation set. The finalsubmission also featured checkpoint averaging within a training run andensemble decoding of models trained during multiple runs. On test data, ourbest single model obtained a BLEU score of 9.7, while the ensemble obtained aBLEU score of 10.24.

Fine-tuning on Clean Data for End-to-End Speech Translation: FBK @ IWSLT 2018