公开(公告)号：WO2023059580A1

公开(公告)日：2023-04-13

申请号：PCT/US2022/045602

申请日：2022-10-04

Applicant: NEC LABORATORIES AMERICA, INC.

Inventor： CHEN, Haifeng ,  YU, Wenchao ,  CHEN, Yuncong ,  CHEN, Zhengzhang ,  ZHANG, Xuchao ,  TANG, LuAn ,  HE, Zexue

IPC: G06F40/58 ,  G06F40/56 ,  G10L15/26 ,  G10L15/00 ,  G06F3/16 ,  G06N20/00 ,  G06N3/04 ,  G06F40/30 ,  G06F40/47 ,  G06N3/08

Abstract: A computer-implemented method for multi-model representation learning is provided. The method includes encoding, by a trained time series (TS) encoder, an input TS segment into a TS-shared latent representation and a TS-private latent representation. The method further includes generating, by a trained text generator, a natural language text that explains the input TS segment, responsive to the TS-shared latent representation, the TS-private latent representation, and a text-private latent representation.