Framework and method for melody generation
OwnerStephen Hahn, Cynthia Rudin +4inventors
InventorsStephen Hahn, Cynthia Rudin, Yue Jiang, Simon Mak, Jerry Yin, Rico Zhu
Life of this patent
Estimating the term…
Abstract
Methods and system for music generation. One method comprises defining a phrase structure and a metrical layout, and generating a melody based on the phrase structure and the metrical layout using a probabilistic model of contour-sequences in a machine learning model. The probabilistic model includes a plurality of production rules determined by the machine learning model trained on a dataset of hierarchical analyses, and the contour-sequences defining directional patterns between musical notes extracted from the dataset of hierarchical analyses.
Claims20
A method for music generation comprising:
- defining a phrase structure and a metrical layout;
- and
- generating, with at least one electronic processor, a melody based on the phrase structure and the metrical layout using a probabilistic model of contour-sequences in a machine learning model, the probabilistic model including a plurality of production rules determined by the machine learning model trained on a dataset of hierarchical analyses, and the contour-sequences defining directional patterns between musical notes extracted from the dataset of hierarchical analyses.
An apparatus comprising:
- at least one processor;
- at least one memory storing instructions executable by the at least one processor;
- and
- a machine learning model comprising a melody generator, wherein the melody generator comprises parameters stored in the at least one memory and is trained to:
- generate a melody based on a phrase structure and a metrical layout using a probabilistic model of contour-sequences, the probabilistic model including a plurality of production rules determined by the machine learning model trained on a dataset of hierarchical analyses, and the contour-sequences defining directional patterns between musical notes extracted from the dataset of hierarchical analyses.
A method for training a music generation model, comprising:
- defining a phrase structure and a metrical layout;
- obtaining training data including a ground-truth middleground harmonic sequence and a ground-truth foreground melody based on a dataset of hierarchical analyses;
- generating a melody based on the phrase structure and the metrical layout using a probabilistic model of contour-sequences in a machine learning model, the probabilistic model including a plurality of production rules and the contour-sequences defining directional patterns between musical notes extracted from the dataset of hierarchical analyses;
- computing a melody loss based on a difference between the generated melody and the ground-truth foreground melody;
- and
- updating parameters of the machine learning model based on the melody loss.
Dependencies are inferred from the claim text.