-
公开(公告)号：US11308146B2
公开(公告)日：2022-04-19
申请号：US16809222
申请日：2020-03-04
Applicant: Adobe Inc.
Inventor： Gaurav Verma , Suryateja B V , Samagra Sharma , Balaji Vasan Srinivasan
IPC: G06F16/48 , G06F40/30 , G06F16/2457 , G06F16/44 , G06F16/435
Abstract: Content fragments aligned to content criteria enable rich sets of multimodal content to be generated based on specified content criteria, such as content needs pertaining to various content delivery platforms and scenarios. For instance, the described techniques take a set of content (e.g., text, images, etc.) along with a specified content criteria (e.g., business/user need) and creates content fragment variants that are tailored to the content criteria with respect to both the information presented as well as the style of the content presented.
-
公开(公告)号：US20190251150A1
公开(公告)日：2019-08-15
申请号：US15897059
申请日：2018-02-14
Applicant: Adobe Inc.
Inventor： Vishwa Vinay , Sopan Khosla , Sanket Vaibhav Mehta , Sahith Thallapally , Gaurav Verma
CPC classification number: G06F17/24 , G06F9/451 , G06F16/3323 , G06F16/93 , G06F17/278 , G06N20/00
Abstract: Techniques and systems are described in which a document management system is configured to update content of document portions of digital documents. In one example, an update to the digital document is initially triggered by a document management system by detecting a triggering change applied to an initial portion of the digital document. The document management system, in response to the triggering change, then determines whether trailing changes are to be made to other document portions, such as to other document portions in the same digital document or another digital document. To do so, triggering and trailing change representations are generated and compared to determine similarity of candidate document portions with an initial document portion.
-
公开(公告)号：US20210264109A1
公开(公告)日：2021-08-26
申请号：US16800018
申请日：2020-02-25
Applicant: Adobe Inc.
IPC: G06F40/253 , G06F40/166 , G06F40/44
Abstract: Rewriting text in the writing style of a target author is described. A stylistic rewriting system receives input text and an indication of the target author. The system trains a language model to understand the target author's writing style using a corpus of text associated with the target author. The language model may be transformer-based, and is first trained on a different corpus of text associated with a range of different authors to understand linguistic nuances of a particular language. Copies of the language model are then cascaded into an encoder-decoder framework, which is further trained using a masked language modeling objective and a noisy version of the target author corpus. After training, the encoder-decoder framework of the trained language model automatically rewrites input text in the writing style of the target author and outputs the rewritten text as stylized text.
-
公开(公告)号：US20230162518A1
公开(公告)日：2023-05-25
申请号：US17534744
申请日：2021-11-24
Applicant: Adobe Inc.
Inventor： Natwar Modani , Vaidehi Ramesh Patil , Inderjeet Jayakumar Nair , Gaurav Verma , Anurag Maurya , Anirudh Kanfade
IPC: G06V30/413 , G06V30/262 , G06V30/414 , G06V30/418
CPC classification number: G06V30/413 , G06V30/274 , G06V30/414 , G06V30/418
Abstract: In implementations of systems for generating indications of relationships between electronic documents, a processing device implements a relationship system to segment text of electronic documents included in a document corpus into segments. The relationship system determines a subset of the electronic documents that includes electronic document pairs having a number of similar segments that is greater than a threshold number. The similar segments are identified using locality sensitive hashing. The electronic document pairs are classified as related documents or unrelated documents using a machine learning model that receives a pair of electronic documents as an input and generates an indication of a classification for the pair of electronic documents as an output. Indications of relationships between particular electronic documents included in the subset are generated based at least partially on the electronic document pairs that are classified as related documents.
-
公开(公告)号：US20210406465A1
公开(公告)日：2021-12-30
申请号：US17467672
申请日：2021-09-07
Applicant: Adobe Inc.
IPC: G06F40/253 , G06F40/44 , G06F40/166
Abstract: Rewriting text in the writing style of a target author is described. A stylistic rewriting system receives input text and an indication of the target author. The system trains a language model to understand the target author's writing style using a corpus of text associated with the target author. The language model may be transformer-based, and is first trained on a different corpus of text associated with a range of different authors to understand linguistic nuances of a particular language. Copies of the language model are then cascaded into an encoder-decoder framework, which is further trained using a masked language modeling objective and a noisy version of the target author corpus. After training, the encoder-decoder framework of the trained language model automatically rewrites input text in the writing style of the target author and outputs the rewritten text as stylized text.
-
Patent Agency Ranking
公开(公告)号：US12198459B2
公开(公告)日：2025-01-14
申请号：US17534744
申请日：2021-11-24
Applicant: Adobe Inc.
Inventor： Natwar Modani , Vaidehi Ramesh Patil , Inderjeet Jayakumar Nair , Gaurav Verma , Anurag Maurya , Anirudh Kanfade
IPC: G06K9/34 , G06V30/19 , G06V30/262 , G06V30/413 , G06V30/414 , G06V30/418
Abstract: In implementations of systems for generating indications of relationships between electronic documents, a processing device implements a relationship system to segment text of electronic documents included in a document corpus into segments. The relationship system determines a subset of the electronic documents that includes electronic document pairs having a number of similar segments that is greater than a threshold number. The similar segments are identified using locality sensitive hashing. The electronic document pairs are classified as related documents or unrelated documents using a machine learning model that receives a pair of electronic documents as an input and generates an indication of a classification for the pair of electronic documents as an output. Indications of relationships between particular electronic documents included in the subset are generated based at least partially on the electronic document pairs that are classified as related documents.
-
公开(公告)号：US11727913B2
公开(公告)日：2023-08-15
申请号：US16725716
申请日：2019-12-23
Applicant: Adobe Inc.
Inventor： Gaurav Verma , Vishwa Vinay , Sneha Chowdary Vinjam , Siddharth Sahay , Mitansh Jain
IPC: G10L15/16 , G10L13/033 , G10L13/00 , G06F16/35 , G10L13/08 , G06F3/0482 , G06F3/16 , G10L13/047
CPC classification number: G10L13/00 , G06F3/0482 , G06F3/167 , G06F16/358 , G10L13/047 , G10L13/08
Abstract: A sound association system identifies one or more aurally active words in digital text. Aurally active words refer to words that denote particular sounds. Context-based sounds corresponding to the one or more aurally active words are also identified. Each context-based sound is anchored to or associated with the corresponding one or more aurally active words and is played back when the digital text is played back or read, providing context-based background sounds associated with the one or more aurally active words. For example, a context-based sound can be played back at a higher volume when the one or more aurally active words are played back or read, and at a lower volume when other words of the digital text are played back or read.
-
公开(公告)号：US11636264B2
公开(公告)日：2023-04-25
申请号：US17467672
申请日：2021-09-07
Applicant: Adobe Inc.
IPC: G06F40/253 , G06F40/44 , G06F40/166 , G06N5/022 , G06F40/169 , G06F40/289 , G06V30/418 , G06N3/045 , G06F18/21 , G06N3/088 , G06F18/214 , G06F40/56 , G06F17/00
Abstract: Rewriting text in the writing style of a target author is described. A stylistic rewriting system receives input text and an indication of the target author. The system trains a language model to understand the target author's writing style using a corpus of text associated with the target author. The language model may be transformer-based, and is first trained on a different corpus of text associated with a range of different authors to understand linguistic nuances of a particular language. Copies of the language model are then cascaded into an encoder-decoder framework, which is further trained using a masked language modeling objective and a noisy version of the target author corpus. After training, the encoder-decoder framework of the trained language model automatically rewrites input text in the writing style of the target author and outputs the rewritten text as stylized text.
-
公开(公告)号：US20220138474A1
公开(公告)日：2022-05-05
申请号：US17090013
申请日：2020-11-05
Applicant: Adobe Inc.
Inventor： Gaurav Verma , Balaji Vasan Srinivasan , Trikay Nalamada , Pranav Goel , Keerti Harpavat , Aman Mishra
IPC: G06K9/00 , G11B27/034 , G11B27/34
Abstract: A method for personalized playback of a video as performed by a video platform includes parsing a video into segments based on visual and audio content of the video. The platform creates multimodal fragments that represent underlying segments of the video, and then orders the multimodal fragments based on a preference of a target user. The platform thus enables nonlinear playback of the segmented video in accordance with the multimodal fragments.
-
公开(公告)号：US11062085B2
公开(公告)日：2021-07-13
申请号：US16694364
申请日：2019-11-25
Applicant: Adobe Inc.
Inventor： Gaurav Verma , Balaji Vasan Srinivasan , Shiv Kumar Saini , Niyati Himanshu Chhaya
IPC: G06F17/00 , G06F40/253 , G06F40/30 , G06F40/166 , G06F40/284
Abstract: A method for generating stylistic feature prescriptions to align a body of text with one or more target goals includes receiving, at a stylistic feature model, a body of text, where the body of text is selected by a user via a graphical user interface (GUI). The stylistic feature model identifies stylistic features from the body of text and populates a stylistic feature vector with the stylistic features. A trained de-confounded prediction model receives the stylistic feature vector. The trained de-confounded prediction model using the stylistic feature vector generates a prediction value for each of one or more target goals, compares the prediction value for each of the one or more target goals to a target value for each of the one or more target goals and outputs, for display on the GUI, one or more stylistic feature prescriptions to the body of text based on results of the comparing.
-
-
-
-
-
-
-
-
-
Search Results
18
records
(took 0.022 seconds)
