The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 24, 2022

Filed:

Dec. 05, 2019
Applicant:

Samsung Electronics Co., Ltd., Suwon-si, KR;

Inventors:

Peter M. Bretan, Novato, CA (US);

Larry P. Heck, Los Altos, CA (US);

Hongxia Jin, San Jose, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10H 1/00 (2006.01); G06N 3/04 (2006.01); G06K 9/62 (2022.01); G06F 16/638 (2019.01);
U.S. Cl.
CPC ...
G10H 1/0025 (2013.01); G06F 16/638 (2019.01); G06K 9/623 (2013.01); G06K 9/6256 (2013.01); G06K 9/6276 (2013.01); G06N 3/0454 (2013.01);
Abstract

A method includes receiving a non-linguistic input associated with an input musical content. The method also includes, using a model that embeds multiple musical features describing different musical content and relationships between the different musical content in a latent space, identifying one or more embeddings based on the input musical content. The method further includes at least one of: (i) identifying stored musical content based on the one or more identified embeddings or (ii) generating derived musical content based on the one or more identified embeddings. In addition, the method includes presenting at least one of: the stored musical content or the derived musical content. The model is generated by training a machine learning system having one or more first neural network components and one or more second neural network components such that embeddings of the musical features in the latent space have a predefined distribution.


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