Attention-based Transformer models have been increasingly employed for automatic music
generation. To condition the generation process of such a model with a user-specified …

This paper, we present the publication of our analysis data and analyzing tool based on the
generative theory of tonal music (GTTM). Musical databases such as score databases …

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 …

We describe and discuss our computer implementations of Lerdahl and Jackendoff's (1983)
Generative Theory of Tonal Music (GTTM). We consider this theory to be one of the most …

An automatic analyzer based on the generative theory of tonal music (GTTM) for acquiring a
time-span tree is described. Although an analyzer based on GTTM was previously reported …

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) …

In this paper, we describe σGTTMⅡ, a method that detects local grouping boundaries of the
generative theory of tonal music (GTTM) based on clustering and statistical learning. It is …

While criteria for Schenkerian analysis have been much discussed, such discussions have
generally not been informed by data. Kirlin [Kirlin, Phillip B., 2014 “A Probabilistic Model of …