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 technique used mel-cepstral features, log spectrum and prosody based features with a non- linear artificial neural network in designing speaker recognition features that minimize telephone handset distortion. Effect of handset distortion was done to maximize speaker recognition performance specifically in the setting of telephone handset mismatch between training and testing as results on the 1998 NIST Speaker Recognition Evaluation corpus shows a high efficiency of 98% performance.

Optimization of Telephone Handset Distortion in Speaker Recognition by Discriminative Feature Design