The dominant approach for music representation learning involves the deep unsupervised
model family variational autoencoder (VAE). However, most, if not all, viable attempts on this …

Heartbeat retains a musical rhythm and music speaks whenever words fail. This paper
provides a systematic review of the papers related to computational musicology. This …

This paper presents a probabilistic formulation of music language modelling based on the
generative theory of tonal music (GTTM) named probabilistic GTTM (PGTTM). GTTM is a …

This paper describes an analyzer that simultaneously learns grouping and metrical
structures on the basis of the generative theory of tonal music (GTTM) by using a deep …

This paper describes an analyzer that automatically generates the metrical structure of a
generative theory of tonal music (GTTM). Although a fully automatic time-span tree analyzer …

This paper proposes a new morphing method to generate a melody, given two melodies
represented by time-span trees obtained from the generative theory of tonal music (GTTM) …

This paper describes an analyzer for detecting local grouping boundaries and generating
metrical structures of music pieces based on a generative theory of tonal music (GTTM) …

Musical grammar describes a set of principles that are used to understand and interpret the
structure of a piece according to a musical style. The main topic of this study is grammar …

This paper describes a time-span tree leveled by the length of the time span. Using the time-
span tree of the Generative Theory of Tonal Music, it is possible to reduce notes in a melody …

This paper describes the" Melody Slot Machine," an interactive music system that enables
control over virtual performers. Conventional virtual players focus on what kind of output …