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

This paper presents a generative AI model for automated music compositionwith LSTM networks that takes a novel approach at encoding musical informationwhich is based on movement in music rather than absolute pitch. Melodies areencoded as a series of intervals rather than a series of pitches, and chordsare encoded as the set of intervals that each chord note makes with the melodyat each timestep. Experimental results show promise as they sound musical andtonal. There are also weaknesses to this method, mainly excessive modulationsin the compositions, but that is expected from the nature of the encoding. Thisissue is discussed later in the paper and is a potential topic for future work.

Differential Music: Automated Music Generation Using LSTM Networks with Representation Based on Melodic and Harmonic Intervals