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 investigates the use of Machine Translation (MT) to bootstrap aNatural Language Understanding (NLU) system for a new language for the use caseof a large-scale voice-controlled device. The goal is to decrease the cost andtime needed to get an annotated corpus for the new language, while still havinga large enough coverage of user requests. Different methods of filtering MTdata in order to keep utterances that improve NLU performance andlanguage-specific post-processing methods are investigated. These methods aretested in a large-scale NLU task with translating around 10 millions trainingutterances from English to German. The results show a large improvement forusing MT data over a grammar-based and over an in-house data collectionbaseline, while reducing the manual effort greatly. Both filtering andpost-processing approaches improve results further.

Selecting Machine-Translated Data for Quick Bootstrapping of a Natural Language Understanding System