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

Audio tagging aims to assign one or several tags to an audio clip. Most ofthe datasets are weakly labelled, which means only the tags of the clip areknown, without knowing the occurrence time of the tags. The labeling of anaudio clip is often based on the audio events in the clip and no event levellabel is provided to the user. Previous works have used the bag of frames modelassume the tags occur all the time, which is not the case in practice. Wepropose a joint detection-classification (JDC) model to detect and classify theaudio clip simultaneously. The JDC model has the ability to attend toinformative and ignore uninformative sounds. Then only informative regions areused for classification. Experimental results on the "CHiME Home" dataset showthat the JDC model reduces the equal error rate (EER) from 19.0% to 16.9%. Moreinterestingly, the audio event detector is trained successfully without needingthe event level label.

A Joint Detection-Classification Model for Audio Tagging of Weakly Labelled Data