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

Audio textures are a subset of environmental sounds, often defined as havingstable statistical characteristics within an adequately large window of timebut may be unstructured locally. They include common everyday sounds such asfrom rain, wind, and engines. Given that these complex sounds contain patternson multiple timescales, they are a challenge to model with traditional methods.We introduce a novel modelling approach for textures, combining recurrentneural networks trained at different levels of abstraction with a conditioningstrategy that allows for user-directed synthesis. We demonstrate the model'sperformance on a variety of datasets, examine its performance on variousmetrics, and discuss some potential applications.

MTCRNN: A multi-scale RNN for directed audio texture synthesis