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    INTENT DETECTION
    4.
    发明申请
    INTENT DETECTION 有权

    公开(公告)号：US20230136527A1

    公开(公告)日：2023-05-04

    申请号：US17453562

    申请日：2021-11-04

    Applicant: ADOBE INC.

    Inventor： Jianguo Zhang ,  Trung Huu Bui ,  Seunghyun Yoon ,  Xiang Chen ,  Quan Hung Tran ,  Walter W. Chang

    IPC: G06F40/40 ,  G06F40/30 ,  G06F40/284 ,  G06V30/19

    Abstract: Systems and methods for natural language processing are described. One or more aspects of a method, apparatus, and non-transitory computer readable medium include receiving a text phrase; encoding the text phrase using an encoder to obtain a hidden representation of the text phrase, wherein the encoder is trained during a first training phrase using self-supervised learning based on a first contrastive loss and during a second training phrase using supervised learning based on a second contrastive learning loss; identifying an intent of the text phrase from a predetermined set of intent labels using a classification network, wherein the classification network is jointly trained with the encoder in the second training phase; and generating a response to the text phrase based on the intent.

    GENERATING SYNTHETIC CODE-SWITCHED DATA FOR TRAINING LANGUAGE MODELS
    8.
    发明公开
    GENERATING SYNTHETIC CODE-SWITCHED DATA FOR TRAINING LANGUAGE MODELS 审中-公开

    公开(公告)号：US20230259718A1

    公开(公告)日：2023-08-17

    申请号：US17651555

    申请日：2022-02-17

    Applicant: Adobe Inc.

    Inventor： Cesa Salaam ,  Seunghyun Yoon ,  Trung Huu Bui ,  Franck Dernoncourt

    IPC: G06F40/58 ,  G06F40/47 ,  G06N3/04 ,  G06N3/08

    CPC classification number: G06F40/58 ,  G06F40/47 ,  G06N3/0454 ,  G06N3/08

    Abstract: Techniques for training a language model for code switching content are disclosed. Such techniques include, in some embodiments, generating a dataset, which includes identifying one or more portions within textual content in a first language, the identified one or more portions each including one or more of offensive content or non-offensive content; translating the identified one or more salient portions to a second language; and reintegrating the translated one or more portions into the textual content to generate code-switched textual content. In some cases, the textual content in the first language includes offensive content and non-offensive content, the identified one or more portions include the offensive content, and the translated one or more portions include a translated version of the offensive content. In some embodiments, the code-switched textual content is at least part of a synthetic dataset usable to train a language model, such as a multilingual classification model.

    VIDEO RECOMMENDER SYSTEM BY KNOWLEDGE BASED MULTI-MODAL GRAPH NEURAL NETWORKS
    9.
    发明公开
    VIDEO RECOMMENDER SYSTEM BY KNOWLEDGE BASED MULTI-MODAL GRAPH NEURAL NETWORKS 审中-公开

    公开(公告)号：US20230237093A1

    公开(公告)日：2023-07-27

    申请号：US17649091

    申请日：2022-01-27

    Applicant: ADOBE INC.

    Inventor： Yifan Li ,  Trung Huu Bui ,  Timothy Jeewun Ganter ,  David Fox

    IPC: G06F16/735 ,  G06N3/08

    CPC classification number: G06F16/735 ,  G06N3/08

    Abstract: Systems and methods for item recommendation are described. Embodiments of the present disclosure receive input indicating a relationship between a user and a first content item; generate a knowledge graph based on the input, wherein the knowledge graph comprises relationship information between the user and a plurality of content items; generate a first feature embedding representing the user and a second feature embedding representing a second content item of the plurality of content items based on the knowledge graph, wherein the second feature embedding is generated using a first modality for a query vector of an attention mechanism and a second modality for a key vector and a value vector of the attention mechanism; compare the first feature embedding to the second feature embedding to obtain a similarity score; and recommend the second content item for the user based on the similarity score.

    Customizable speech recognition system
    10.
    发明授权
    Customizable speech recognition system 有权

    公开(公告)号：US11538463B2

    公开(公告)日：2022-12-27

    申请号：US16383312

    申请日：2019-04-12

    Applicant: ADOBE INC.

    Inventor： Trung Huu Bui ,  Subhadeep Dey ,  Franck Dernoncourt

    IPC: G10L15/16 ,  G06N3/08 ,  G10L15/07

    Abstract: Methods and systems are provided for generating a customized speech recognition neural network system comprised of an adapted automatic speech recognition neural network and an adapted language model neural network. The automatic speech recognition neural network is first trained in a generic domain and then adapted to a target domain. The language model neural network is first trained in a generic domain and then adapted to a target domain. Such a customized speech recognition neural network system can be used to understand input vocal commands.

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