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公开(公告)号:US20230214600A1
公开(公告)日:2023-07-06
申请号:US18182068
申请日:2023-03-10
Applicant: Adobe Inc.
Inventor: Zhe LIN , Walter W. CHANG , Scott COHEN , Khoi Viet PHAM , Jonathan BRANDT , Franck DERNONCOURT
IPC: G06F40/30 , G06F16/532 , G06F16/55 , G06N5/02 , G06N5/04 , G06F40/205 , G06F40/295 , G06N20/00
CPC classification number: G06F40/30 , G06F16/532 , G06F16/55 , G06N5/02 , G06N5/04 , G06F40/205 , G06F40/295 , G06N20/00
Abstract: Embodiments of the present invention provide systems, methods, and non-transitory computer storage media for parsing a given input referring expression into a parse structure and generating a semantic computation graph to identify semantic relationships among and between objects. At a high level, when embodiments of the preset invention receive a referring expression, a parse tree is created and mapped into a hierarchical subject, predicate, object graph structure that labeled noun objects in the referring expression, the attributes of the labeled noun objects, and predicate relationships (e.g., verb actions or spatial propositions) between the labeled objects. Embodiments of the present invention then transform the subject, predicate, object graph structure into a semantic computation graph that may be recursively traversed and interpreted to determine how noun objects, their attributes and modifiers, and interrelationships are provided to downstream image editing, searching, or caption indexing tasks.
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公开(公告)号:US20250131182A1
公开(公告)日:2025-04-24
申请号:US18983114
申请日:2024-12-16
Applicant: Adobe Inc.
Inventor: Amirreza SHIRANI , Franck DERNONCOURT , Jose Ignacio ECHEVARRIA VALLESPI , Paul ASENTE , Nedim LIPKA , Thamar I. SOLORIO MARTINEZ
IPC: G06F40/109 , G06F40/169 , G06N3/02
Abstract: Embodiments are disclosed for recommending fonts based on text inputs are described. In some embodiments, a method of recommending fonts includes receiving a selection of text, providing a representation of the selection of text to a font recommendation model, generating, by the font recommendation model, a prediction score for each of a plurality of fonts based on the representation of the selection of text, and returning at least one recommended font based on the prediction score for each of the plurality of fonts.
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公开(公告)号:US20250005691A1
公开(公告)日:2025-01-02
申请号:US18344203
申请日:2023-06-29
Applicant: Adobe Inc.
Inventor: Nedim LIPKA , Ryan ROSSI , Jianna Audrey Reyes SO , Franck DERNONCOURT , Alexa SIU
IPC: G06Q50/18
Abstract: A method includes extracting an action from a document using a machine learning model. The action is associated with an action parameter. The method further includes extracting a plurality of action events corresponding to the action from the document using the machine learning model. The method further includes generating a record associated with the document based on the extracted action. The method further includes populating the record with the action parameter. The method further includes executing an action event in the plurality of action events using the record.
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公开(公告)号:US20240257798A1
公开(公告)日:2024-08-01
申请号:US18104434
申请日:2023-02-01
Applicant: ADOBE INC.
Inventor: Oriol NIETO-CABALLERO , Zeyu JIN , Justin Jonathan SALAMON , Franck DERNONCOURT
CPC classification number: G10L15/005 , G10L25/30
Abstract: Some aspects of the technology described herein employ a neural network with an efficient and lightweight architecture to perform spoken language recognition. Given an audio signal comprising speech, features are generated from the audio signal, for instance, by converting the audio signal to a normalized spectrogram. The features are input to the neural network, which has one or more convolutional layers and an output activation layer. Each neuron of the output activation layer corresponds to a language from a set of language and generates an activation value. Based on the activations values, an indication of zero or more languages from the set of languages is provided for the audio signal.
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公开(公告)号:US20220358280A1
公开(公告)日:2022-11-10
申请号:US17489474
申请日:2021-09-29
Applicant: Adobe Inc.
Inventor: Amirreza SHIRANI , Franck DERNONCOURT , Jose Ignacio ECHEVARRIA VALLESPI , Paul ASENTE , Nedim LIPKA , Thamar I. SOLORIO MARTINEZ
IPC: G06F40/109 , G06F40/169 , G06N3/02
Abstract: Embodiments are disclosed for recommending fonts based on text inputs are described. In some embodiments, a method of recommending fonts includes receiving a selection of text, providing a representation of the selection of text to a font recommendation model, generating, by the font recommendation model, a prediction score for each of a plurality of fonts based on the representation of the selection of text, and returning at least one recommended font based on the prediction score for each of the plurality of fonts.
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