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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

We propose a dataset, AVASpeech-SMAD, to assist speech and music activitydetection research. With frame-level music labels, the proposed dataset extendsthe existing AVASpeech dataset, which originally consists of 45 hours of audioand speech activity labels. To the best of our knowledge, the proposedAVASpeech-SMAD is the first open-source dataset that features strong polyphoniclabels for both music and speech. The dataset was manually annotated andverified via an iterative cross-checking process. A simple automaticexamination was also implemented to further improve the quality of the labels.Evaluation results from two state-of-the-art SMAD systems are also provided asa benchmark for future reference.

AVASpeech-SMAD: A Strongly Labelled Speech and Music Activity Detection Dataset with Label Co-Occurrence