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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

When working with oral speech, the issue of natural meaning processing can be improved using easily available prosodic information. Only recently, semanticists have started to consider that the prosodic features could play a key role in the interpretation and classification of different wordâs uses. In this work, we propose a prosodic based automatic system that allows to classify the French word âouiâ into one of the classes âconvictionâ or âlack of convictionâ. To that aim, a questionnaire inspired from opinion polls has been created and permitted to obtain 118 occurrences for both classes of âouiâ. Combined with feature selection procedure, the best classification rates decreases from 85.45% (speaker dependent mode) to 79.25% (speaker independent mode which is closer to an application). Interestingly, we also introduce the âshuttleâ principle that seeks to validate the semantic interpretation thanks to prosodic analysis.

Prosody based Automatic Classification of the Uses of French ‘Oui’ as Convinced or Unconvinced Uses