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:
Jul. 12, 2016

Filed:

Oct. 27, 2015
Applicant:

Northwestern University, Evanston, IL (US);

Inventors:

Mark B. Cartwright, Chicago, IL (US);

Bryan A Pardo, Evanston, IL (US);

Assignee:

NORTHWESTERN UNIVERSITY, Evanston, IL (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10H 1/06 (2006.01); G10H 1/00 (2006.01); G10H 1/36 (2006.01); G06F 17/30 (2006.01);
U.S. Cl.
CPC ...
G10H 1/0008 (2013.01); G06F 17/3053 (2013.01); G06F 17/30743 (2013.01); G10H 1/365 (2013.01); G10H 1/366 (2013.01); G10H 2210/105 (2013.01); G10H 2220/106 (2013.01); G10H 2240/145 (2013.01); G10H 2250/615 (2013.01);
Abstract

Systems, methods, and apparatus for equalization preference learning are provided. An example method includes receiving an audio input with respect to a target sound. The example method includes extracting one or more features from the audio input to provide one or more examples for rating based on the audio input. The example method includes generating a query based on the audio input and the one or more rated examples. The example method includes providing one or more synthesizer suggestion results identified in a search based on the query. The example method includes evaluating the one or more results with respect to the target sound. When one of the results matches the target sound, the example method includes outputting synthesizer parameters associated with the result. When none of the results matches the target sound, the example method includes refining the query for a second search based on feedback with respect to the one or more results.


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