Music has always been an essential aspect of human culture, and the methods for its
creation and analysis have evolved alongside the advancement of computational …

In this article, we explore the usage of long short-term memory neural network (NN) in
generating music pieces and propose an approach to do so. Bach's musical style has been …

Existing recurrent neural language models often fail to capture higher-level structure present
in text: for example, rhyming patterns present in poetry. Much prior work on poetry …

In this study, we sought to objectively and quantitatively characterize the prosodic features of
autism spectrum disorder (ASD) via the characteristics of prosody in a newly developed …

Music language models play an important role for various music signal and symbolic music
processing tasks, such as music generation, symbolic music classification, or automatic …

This paper presents MahlerNet, a deep recurrent neural network that models polyphonic
music sequences of arbitrary length with an arbitrary number of instruments. The data …

Existing kinematic research on orchestral conducting movement contributes to beat-tracking
and the delivery of performance dynamics. Methodologically, such movement cues have …

This paper addresses the problem of unsupervised parts-aware point cloud generation with
learned parts-based self-similarity. Our SPA-VAE infers a set of latent canonical candidate …

The element-wise attention mechanism has been widely used in modern sequence models
for text and music. The original attention mechanism focuses on token-level similarity to …

People need to get relieve from their stress and thoughts by engaging themselves with
entertainment. Music plays a vital role in changing the people environment to overcome their …