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

We present an end-to-end approach to extract semantic concepts directly fromthe speech audio signal. To overcome the lack of data available for this spokenlanguage understanding approach, we investigate the use of a transfer learningstrategy based on the principles of curriculum learning. This approach allowsus to exploit out-of-domain data that can help to prepare a fully neuralarchitecture. Experiments are carried out on the French MEDIA and PORTMEDIAcorpora and show that this end-to-end SLU approach reaches the best resultsever published on this task. We compare our approach to a classical pipelineapproach that uses ASR, POS tagging, lemmatizer, chunker... and other NLP toolsthat aim to enrich ASR outputs that feed an SLU text to concepts system. Last,we explore the promising capacity of our end-to-end SLU approach to address theproblem of domain portability.

Curriculum-based transfer learning for an effective end-to-end spoken language understanding and domain portability