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

Production and perception experiments were conducted to examine whether focus prosody varies by phrase-initial tones in Seoul Korean. We also trained an automatic classifier to locate prosodic focus within a sentence. Overall, focus prosody in Seoul Korean was weak and confusing in production, and poorly identified in perception. However, Seoul Korean’s focus prosody differed between phrase-initial low and high tones. The low tone group induced a smaller pitch increase by focus than the high tone group. The low tone group was also subject to a greater degree of confusion, although both tone groups showed some degree of confusion spanning the entire phrase as a focus effect. The identification rate was, therefore, approximately half in the low tone group (23.5%) compared to the high tone group (40%). In machine classification, the high tone group was also more accurately identified (high: 86% vs. low: 68%) when trained separately, and the machine’s general performance when the two tone groups were trained together was much superior to the human’s (machine: 65% vs. human: 32%). Although the focus prosody in Seoul Korean was weak and confusing, the identification rate of focus was higher under certain circumstances, which avers that focus prosody can vary within a single language.

Focus Prosody Varies by Phrase-Initial Tones in Seoul Korean: Production, Perception, and Automatic Classification