公开(公告)号：US20230386437A1

公开(公告)日：2023-11-30

申请号：US17804198

申请日：2022-05-26

Applicant: Lemon Inc.

Inventor： Ju-Chiang Wang ,  Yun-Ning Hung ,  Jordan Smith

IPC: G10H1/00 ,  G06N3/08

CPC classification number: G10H1/0008 ,  G06N3/08 ,  G10H2210/056

Abstract: System and methods directed to identifying music theory labels for audio tracks are described. More specifically, a first training set of audio portions may be generated from a plurality of audio tracks, segments within the plurality of audio tracks being labeled according to a plurality of music theory labels. A deep neural network model may then be trained using the first training set as an input, a first loss function for music theory label identifications of audio portions of the first training set, and a second loss function for segment boundary identifications within the audio portions of the first training set. In examples, the music theory label identifications and the segment boundary identifications are generated by the deep neural network model. A first audio track is received and segment boundary identifications and music theory labels for segments within the first audio track are generated using the deep neural network model.