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

In language modeling based music generation, a generated waveform isrepresented by a sequence of hierarchical token stacks that can be decodedeither in an auto-regressive manner or in parallel, depending on the codebookpatterns. In particular, flattening the codebooks represents the highestquality decoding strategy, while being notoriously slow. To this end, wepropose a novel stack-and-delay style of decoding strategy to improve upon theflat pattern decoding where generation speed is four times faster as opposed tovanilla flat decoding. This brings the inference time close to that of thedelay decoding strategy, and allows for faster inference on GPU for small batchsizes. For the same inference efficiency budget as the delay pattern, we showthat the proposed approach performs better in objective evaluations, almostclosing the gap with the flat pattern in terms of quality. The results arecorroborated by subjective evaluations which show that samples generated by thenew model are slightly more often preferred to samples generated by thecompeting model given the same text prompts.

Stack-and-Delay: a new codebook pattern for music generation