公开(公告)号：US20240282345A1

公开(公告)日：2024-08-22

申请号：US18413991

申请日：2024-01-16

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Yoonhyung KIM ,  Byung Ok KANG ,  Hoon CHUNG

IPC: G11B27/10 ,  G06V10/20 ,  G06V20/40 ,  G10L25/30

CPC classification number: G11B27/10 ,  G06V10/20 ,  G06V20/40 ,  G10L25/30

Abstract: Disclosed herein are an apparatus and method for audio-video sampling frequency ratio unification, including memory configured to store at least one program, and a processor configured to execute the program, wherein the program is configured to perform receiving an audio signal and a video signal, adjusting a ratio of a sampling frequency of the audio signal to a sampling frequency of the video signal so that the sampling frequency ratio is constant based on a deep learning network, and outputting an adjusted audio signal and the video signal.

公开(公告)号：US20240105166A1

公开(公告)日：2024-03-28

申请号：US18350111

申请日：2023-07-11

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Hoon CHUNG ,  Byung Ok KANG ,  Yoonhyung KIM

IPC: G10L15/16 ,  G10L15/06 ,  G10L15/065

CPC classification number: G10L15/16 ,  G10L15/063 ,  G10L15/065

Abstract: Provided is a self-supervised learning method based on permutation invariant cross entropy. A self-supervised learning method based on permutation invariant cross entropy performed by an electronic device includes: defining a cross entropy loss function for pre-training of an end-to-end speech recognition model; configuring non-transcription speech corpus data composed only of speech as input data of the cross entropy loss function; setting all permutations of classes included in the non-transcription speech corpus data as an output target and calculating cross entropy losses for each class; and determining a minimum cross entropy loss among the calculated cross entropy losses for each class as a final loss.