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

Automatic analysis of poetic rhythm is a challenging task that involveslinguistics, literature, and computer science. When the language to be analyzedis known, rule-based systems or data-driven methods can be used. In this paper,we analyze poetic rhythm in English and Spanish. We show that therepresentations of data learned from character-based neural models are moreinformative than the ones from hand-crafted features, and that aBi-LSTM+CRF-model produces state-of-the art accuracy on scansion of poetry intwo languages. Results also show that the information about whole wordstructure, and not just independent syllables, is highly informative forperforming scansion.

A Comparison of Feature-Based and Neural Scansion of Poetry