公开(公告)号：US20250061917A1

公开(公告)日：2025-02-20

申请号：US18235372

申请日：2023-08-18

Applicant: Google LLC

Inventor： Josh Belanich ,  Taesik Gong ,  Krishna Somandepalli ,  Brian Eoff ,  Brendan Wesley Jou ,  Arsha Nagrani

IPC: G10L25/63 ,  G10L15/06

Abstract: The technology relates to enhancing speech emotion recognition models with methods that enable the use of unlabeled data by inferring weak emotion labels. This is done by pre-trained large language models through weakly-supervised learning. For inferring weak labels constrained to a taxonomy, a textual entailment approach selects an emotion label with the highest entailment score for a speech transcript extracted via automatic speech recognition. The system may employ a method that generates, by one or more processors, a text transcript for a snippet of input speech, and then applies the text transcript to a pre-trained language model. The system can generate, using the pre-trained language model according to an engineered prompt and a predetermined taxonomy, a textual entailment from the text transcript. Based on this, the system may generate, by the one or more processors using the textual entailment, a predicted emotion corresponding to the input speech.

公开(公告)号：US20230297852A1

公开(公告)日：2023-09-21

申请号：US18007379

申请日：2021-07-29

Applicant: Google LLC

Inventor： Li Zhang ,  Andrew Gerald Howard ,  Brendan Wesley Jou ,  Yukun Zhu ,  Mingda Zhang ,  Andrey Zhmoginov

IPC: G06N5/022

CPC classification number: G06N5/022

Abstract: Example implementations of the present disclosure combine efficient model design and dynamic inference. With a standalone lightweight model, the unnecessary computation on easy examples is avoided and the information extracted by the lightweight model also guide the synthesis of a specialist network from the basis models. With extensive experiments on ImageNet it is shown that a proposed example BasisNet is particularly effective for image classification and a BasisNet-MV3 achieves 80.3% top-1 accuracy with 290 M MAdds without early termination.