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:
Apr. 14, 2026

Filed:

Dec. 22, 2022
Applicant:

Acv Auctions Inc., Buffalo, NY (US);

Inventors:

Philip Schneider, Amherst, NY (US);

Michael Pokora, Tonawanda, NY (US);

Justas Birgiolas, Lockport, NY (US);

Livio Forte, III, Lloyd Harbor, NY (US);

Dennis Christopher Fedorishin, East Amherst, NY (US);

Assignee:

ACV Auctions Inc., Buffalo, NY (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G10L 25/78 (2013.01); G01M 13/028 (2019.01); G01M 15/02 (2006.01); G01M 15/12 (2006.01); G10L 25/30 (2013.01);
U.S. Cl.
CPC ...
G10L 25/78 (2013.01); G01M 13/028 (2013.01); G01M 15/02 (2013.01); G01M 15/12 (2013.01); G10L 25/30 (2013.01);
Abstract

Techniques for using a trained machine learning (ML) model to detect presence of vehicle defects from audio acquired at least in part during operation of an engine of a vehicle. The techniques include using at least one computer hardware processor to perform: obtaining, via at least one communication network, a first audio recording that was acquired, using at least one acoustic sensor, at least in part during operation of the engine; processing the first audio recording using the trained ML model to detect, from the first audio recording, presence of at least one vehicle defect, the processing comprising: generating an audio waveform from the first audio recording, generating a two-dimensional (2D) representation of the audio waveform, and processing the audio waveform and the 2D representation of the audio waveform using the trained ML model to obtain output indicative of presence or absence of the at least one vehicle defect.


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