公开(公告)号：US20230162725A1

公开(公告)日：2023-05-25

申请号：US17534221

申请日：2021-11-23

Applicant: Adobe Inc. ,  The Trustees of Princeton University

Inventor： Zeyu JIN ,  Jiaqi SU ,  Adam FINKELSTEIN

IPC: G10L15/16 ,  G10L15/06 ,  G06N3/04

CPC classification number: G10L15/16 ,  G10L15/063 ,  G06N3/0454

Abstract: Embodiments are disclosed for generating full-band audio from narrowband audio using a GAN-based audio super resolution model. A method of generating full-band audio may include receiving narrow-band input audio data, upsampling the narrow-band input audio data to generate upsampled audio data, providing the upsampled audio data to an audio super resolution model, the audio super resolution model trained to perform bandwidth expansion from narrow-band to wide-band, and returning wide-band output audio data corresponding to the narrow-band input audio data.

公开(公告)号：US20240331720A1

公开(公告)日：2024-10-03

申请号：US18191763

申请日：2023-03-28

Applicant: Adobe Inc. ,  The Trustees of Princeton University

Inventor： Zeyu JIN ,  Jiaqi SU ,  Adam FINKELSTEIN

IPC: G10L21/034 ,  G06N5/022 ,  G10L21/0232 ,  G10L25/18 ,  G10L25/24 ,  G10L25/60

CPC classification number: G10L21/034 ,  G06N5/022 ,  G10L21/0232 ,  G10L25/18 ,  G10L25/24 ,  G10L25/60 ,  G10L21/0364 ,  G10L25/30

Abstract: Embodiments are disclosed for converting audio data to studio quality audio data. The method includes obtaining an audio data having a first quality for conversion to studio quality audio. A first machine learning model predicts a set of acoustic features. A spectral mask is applied to the audio data during the prediction of the set of acoustic features. A second machine learning model generates studio quality audio from the set of acoustic features and the audio data.