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

In this paper, we describe our end-to-end multilingual speech translationsystem submitted to the IWSLT 2021 evaluation campaign on the MultilingualSpeech Translation shared task. Our system is built by leveraging transferlearning across modalities, tasks and languages. First, we leveragegeneral-purpose multilingual modules pretrained with large amounts ofunlabelled and labelled data. We further enable knowledge transfer from thetext task to the speech task by training two tasks jointly. Finally, ourmultilingual model is finetuned on speech translation task-specific data toachieve the best translation results. Experimental results show our systemoutperforms the reported systems, including both end-to-end and cascaded basedapproaches, by a large margin.  In some translation directions, our speech translation results evaluated onthe public Multilingual TEDx test set are even comparable with the ones from astrong text-to-text translation system, which uses the oracle speechtranscripts as input.

FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task