公开(公告)号：US20220375462A1

公开(公告)日：2022-11-24

申请号：US17874826

申请日：2022-07-27

Applicant: Samsung Electronics Co., Ltd.

Inventor： Sourav BHATTACHARYA ,  Abhinav MEHROTRA ,  Alberto Gil C. P. RAMOS

IPC: G10L15/16 ,  G10L21/0208

Abstract: Broadly speaking, the present techniques provide methods for conditioning a neural network, which not only improve the generalizable performance of conditional neural networks, but also reduce model size and latency significantly. The resulting conditioned neural network is suitable for on-device deployment due to having a significantly lower model size, lower dynamic memory requirement, and lower latency.

公开(公告)号：US20230410818A1

公开(公告)日：2023-12-21

申请号：US18220567

申请日：2023-07-11

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Alberto Gil C. P. RAMOS ,  Abhinav MEHROTRA ,  Sourav BHATTACHARYA

IPC: G10L17/18 ,  G10L17/04 ,  G10L21/0208 ,  G10L13/08

CPC classification number: G10L17/18 ,  G10L13/08 ,  G10L21/0208 ,  G10L17/04

Abstract: Broadly speaking, embodiments of the present techniques provide a method and system for personalising machine learning models on resource-constrained devices by using conditional neural networks. In particular, the present techniques allow for resource-efficient use of a conditioning vector by incorporating the conditioning vector into weights learned during training. This reduces the computational resources required at inference time.