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. 21, 2026

Filed:

Jan. 11, 2024
Applicant:

Nvidia Corporation, Santa Clara, CA (US);

Inventors:

Taejin Park, San Jose, CA (US);

Ante Jukic, Culver City, CA (US);

He Huang, Greenville, SC (US);

Venkata Naga Krishna Chaitanya Puvvada, San Jose, CA (US);

Kunal Dhawan, San Jose, CA (US);

Nithin Rao Koluguri, Milpitas, CA (US);

Nikolay Karpov, Moscow, AM;

Aleksandr Laptev, Erevan, AM;

Jagadeesh Balam, Campbell, CA (US);

Assignee:

NVIDIA Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 17/18 (2013.01); G10L 17/02 (2013.01); G10L 17/20 (2013.01); G10L 25/30 (2013.01); G10L 25/78 (2013.01);
U.S. Cl.
CPC ...
G10L 17/18 (2013.01); G10L 17/02 (2013.01); G10L 17/20 (2013.01); G10L 25/30 (2013.01); G10L 25/78 (2013.01); G10L 2025/783 (2013.01);
Abstract

Disclosed are apparatuses, systems, and techniques that may use machine learning for implementing speaker recognition, verification, and/or diarization. The techniques include processing audio data channels (ADCs) using a voice detection model to determine voice activity likelihoods (VALs) that individual ADCs include speech, obtaining, using VALs, a second set of ADC(s), and processing, using an audio processing a neural network (NN) model, the second set of ADCs to obtain association of the speech to the one or more speakers. The techniques also include generating a plurality of embeddings associated with the ADCs, processing the plurality of embeddings to obtain aggregated embedding(s) that represent audio data of multiple ADCs, and processing the aggregated embedding(s), using the audio processing NN model, to obtain association of the speech to the one or more speakers.


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