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 Signal Processing Grand Challenge (SPGC) targets a difficult automaticprediction problem of societal and medical relevance, namely, the detection ofAlzheimer's Dementia (AD). Participants were invited to employ signalprocessing and machine learning methods to create predictive models based onspontaneous speech data. The Challenge has been designed to assess the extentto which predictive models built based on speech in one language (English)generalise to another language (Greek). To the best of our knowledge no workhas investigated acoustic features of the speech signal in multilingual ADdetection. Our baseline system used conventional machine learning algorithmswith Active Data Representation of acoustic features, achieving accuracy of73.91% on AD detection, and 4.95 root mean squared error on cognitive scoreprediction.

Multilingual Alzheimer's Dementia Recognition through Spontaneous Speech: a Signal Processing Grand Challenge