Patents by Inventor Niyati Himanshu Chhaya
Niyati Himanshu Chhaya has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240119220Abstract: Systems and methods for text simplification are described. Embodiments of the present disclosure identify a simplified text that includes original information from a complex text and additional information that is not in the complex text. Embodiments then compute an entailment score for each sentence of the simplified text using a neural network, wherein the entailment score indicates whether the sentence of the simplified text includes information from a sentence of the complex text corresponding to the sentence of the simplified text. Then, embodiments generate a modified text based on the entailment score, the simplified text, and the complex text, wherein the modified text includes the original information and excludes the additional information. Embodiments may then present the modified text to a user via a user interface.Type: ApplicationFiled: October 11, 2022Publication date: April 11, 2024Inventors: Vinay Aggarwal, Aparna Garimella, Ananya Ganesh, Niyati Himanshu Chhaya, Nandakishore Kambhatla
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Patent number: 11954431Abstract: Embodiments are disclosed for generating an intelligent change summary are described. In some embodiments, a method of generating an intelligent change summary includes obtaining a representation of a plurality of versions of a document, determining a distance score based on a comparison of a first of version of the document and a second version of the document, the distance score representing a magnitude of changes made from the first version of the document to the second version of the document, and generating a change summary of the document based on the distance score.Type: GrantFiled: November 9, 2021Date of Patent: April 9, 2024Assignee: Adobe Inc.Inventors: Suryateja Bv, Vishwa Vinay, Niyati Himanshu Chhaya, Navita Goyal, Elaine Chao, Balaji Vasan Srinivasan, Aparna Garimella
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Publication number: 20240095440Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating generation and presentation of insights. In one implementation, a set of data is used to generate a data visualization. A candidate insight associated with the data visualization is generated, the candidate insight being generated in text form based on a text template and comprising a descriptive insight, a predictive insight, an investigative, or a prescriptive insight. A set of natural language insights is generated, via a machine learning model. The natural language insights represent the candidate insight in a text style that is different from the text template. A natural language insight having the text style corresponding with a desired text style is selected for presenting the candidate insight and, thereafter, the selected natural language insight and data visualization are providing for display via a graphical user interface.Type: ApplicationFiled: October 11, 2023Publication date: March 21, 2024Inventors: Md Main Uddin RONY, Fan DU, Iftikhar Ahamath BURHANUDDIN, Ryan ROSSI, Niyati Himanshu CHHAYA, Eunyee KOH
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Patent number: 11914951Abstract: Techniques for template generation from image content include extracting information associated with an input image. The information comprises: 1) layout information indicating positions of content corresponding to a content type of a plurality of content types within the input image; and 2) text attributes indicating at least a font of text included in the input image. A user-editable template having the characteristics of the input image is generated based on the layout information and the text attributes.Type: GrantFiled: February 16, 2023Date of Patent: February 27, 2024Assignee: Adobe Inc.Inventors: Vinay Aggarwal, Vishwa Vinay, Rizurekh Saha, Prabhat Mahapatra, Niyati Himanshu Chhaya, Harshit Agrawal, Chloe McConnell, Bhanu Prakash Reddy Guda, Balaji Vasan Srinivasan
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Patent number: 11886480Abstract: Certain embodiments involve using a gated convolutional encoder-decoder framework for applying affective characteristic labels to input text. For example, a method for identifying an affect label of text with a gated convolutional encoder-decoder model includes receiving, at a supervised classification engine, extracted linguistic features of an input text and a latent representation of an input text. The method also includes predicting, by the supervised classification engine, an affect characterization of the input text using the extracted linguistic features and the latent representation. Predicting the affect characterization includes normalizing and concatenating a linguistic feature representation generated from the extracted linguistic features with the latent representation to generate an appended latent representation. The method also includes identifying, by a gated convolutional encoder-decoder model, an affect label of the input text using the predicted affect characterization.Type: GrantFiled: August 29, 2022Date of Patent: January 30, 2024Assignee: ADOBE INC.Inventors: Kushal Chawla, Niyati Himanshu Chhaya, Sopan Khosla
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Publication number: 20230419666Abstract: Techniques are described that support automated generation of a digital document from digital videos using machine learning. The digital document includes textual components that describe a sequence of entity and action descriptions from the digital video. These techniques are usable to generate a single digital document based on a plurality of digital videos as well as incorporate user-specified constraints in the generation of the digital document.Type: ApplicationFiled: September 11, 2023Publication date: December 28, 2023Applicant: Adobe Inc.Inventors: Niyati Himanshu Chhaya, Tripti Shukla, Jeevana Kruthi Karnuthala, Bhanu Prakash Reddy Guda, Ayudh Saxena, Abhinav Bohra, Abhilasha Sancheti, Aanisha Bhattacharyya
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Patent number: 11829705Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating generation and presentation of insights. In one implementation, a set of data is used to generate a data visualization. A candidate insight associated with the data visualization is generated, the candidate insight being generated in text form based on a text template and comprising a descriptive insight, a predictive insight, an investigative, or a prescriptive insight. A set of natural language insights is generated, via a machine learning model. The natural language insights represent the candidate insight in a text style that is different from the text template. A natural language insight having the text style corresponding with a desired text style is selected for presenting the candidate insight and, thereafter, the selected natural language insight and data visualization are providing for display via a graphical user interface.Type: GrantFiled: September 21, 2022Date of Patent: November 28, 2023Assignee: Adobe Inc.Inventors: Md Main Uddin Rony, Fan Du, Iftikhar Ahamath Burhanuddin, Ryan Rossi, Niyati Himanshu Chhaya, Eunyee Koh
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Patent number: 11783584Abstract: Techniques are described that support automated generation of a digital document from digital videos using machine learning. The digital document includes textual components that describe a sequence of entity and action descriptions from the digital video. These techniques are usable to generate a single digital document based on a plurality of digital videos as well as incorporate user-specified constraints in the generation of the digital document.Type: GrantFiled: March 10, 2022Date of Patent: October 10, 2023Assignee: Adobe Inc.Inventors: Niyati Himanshu Chhaya, Tripti Shukla, Jeevana Kruthi Karnuthala, Bhanu Prakash Reddy Guda, Ayudh Saxena, Abhinav Bohra, Abhilasha Sancheti, Aanisha Bhattacharyya
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Publication number: 20230290146Abstract: Techniques are described that support automated generation of a digital document from digital videos using machine learning. The digital document includes textual components that describe a sequence of entity and action descriptions from the digital video. These techniques are usable to generate a single digital document based on a plurality of digital videos as well as incorporate user-specified constraints in the generation of the digital document.Type: ApplicationFiled: March 10, 2022Publication date: September 14, 2023Applicant: Adobe Inc.Inventors: Niyati Himanshu Chhaya, Tripti Shukla, Jeevana Kruthi Karnuthala, Bhanu Prakash Reddy Guda, Ayudh Saxena, Abhinav Bohra, Abhilasha Sancheti, Aanisha Bhattacharyya
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Publication number: 20230196008Abstract: Techniques for template generation from image content includes extracting information associated with an input image. The information comprises: 1) layout information indicating positions of content corresponding to a content type of a plurality of content types within the input image; and 2) text attributes indicating at least a font of text included in the input image.Type: ApplicationFiled: February 16, 2023Publication date: June 22, 2023Inventors: Vinay Aggarwal, Vishwa Vinay, Rizurekh Saha, Prabhat Mahapatra, Niyati Himanshu Chhaya, Harshit Agrawal, Chloe McConnell, Bhanu Prakash Reddy Guda, Balaji Vasan Srinivasan
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Publication number: 20230141448Abstract: Embodiments are disclosed for generating an intelligent change summary are described. In some embodiments, a method of generating an intelligent change summary includes obtaining a representation of a plurality of versions of a document, determining a distance score based on a comparison of a first of version of the document and a second version of the document, the distance score representing a magnitude of changes made from the first version of the document to the second version of the document, and generating a change summary of the document based on the distance score.Type: ApplicationFiled: November 9, 2021Publication date: May 11, 2023Applicant: Adobe Inc.Inventors: Suryateja BV, Vishwa VINAY, Niyati Himanshu CHHAYA, Navita GOYAL, Elaine CHAO, Balaji Vasan SRINIVASAN, Aparna GARIMELLA
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Publication number: 20230137209Abstract: A text style transfer system is described that generates different stylized versions of input text by rewriting the input text according to a target style. To do so, the text style transfer system employs a variational autoencoder to derive separate content and style representations for the input text, where the content representation specifies semantic information conveyed by the input text and the style representation specifies one or more style attributes expressed by the input text. The style representation using counterfactual reasoning to identify different transfer strengths for applying the target style to the input text. Each transfer strength represents a minimum change to the input text that achieves a different expression of the target style. The transfer strengths are then used to generate style representation variants, which are each concatenated with the content representation of the input text to generate the plurality of different stylized versions of the input text.Type: ApplicationFiled: November 3, 2021Publication date: May 4, 2023Applicant: Adobe Inc.Inventors: Sharmila Reddy Nangi, Niyati Himanshu Chhaya, Hyman Chung, Harshit Nyati, Nikhil Kaushik, Sopan Khosla
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Publication number: 20230121711Abstract: A content generator system receives a request to generate content for a target entity, and one or more keywords. The content generator system retrieves, for the target entity, a current stage identifier linking the target entity to a current stage within a multi-stage objective. The content generator system generates an input vector including the current stage identifier, a target stage identifier, a token embedding comprising the one or more keywords, and a position embedding for each of the one or more keywords, the target stage identifier associated with a target stage within the multi-stage objective different from the current stage. The content generator system generates output text content for the target entity by applying a generative transformer network to the input vector. The content generator system transmits the output text content to a computing device associated with the target entity.Type: ApplicationFiled: October 14, 2021Publication date: April 20, 2023Inventors: Niyati Himanshu Chhaya, Udit Kalani, Roodram Paneri, Sreekanth Reddy, Niranjan Kumbi, Navita Goyal, Balaji Vasan Srinivasan, Ayush Agarwal
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Publication number: 20230114742Abstract: Techniques for template generation from image content includes extracting information associated with an input image. The information comprises: 1) layout information indicating positions of content corresponding to a content type of a plurality of content types within the input image; and 2) text attributes indicating at least a font of text included in the input image.Type: ApplicationFiled: October 7, 2021Publication date: April 13, 2023Inventors: Vinay Aggarwal, Vishwa Vinay, Rizurekh Saha, Prabhat Mahapatra, Niyati Himanshu Chhaya, Harshit Agrawal, Chloe McConnell, Bhanu Prakash Reddy Guda, Balaji Vasan Srinivasan
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Patent number: 11610054Abstract: Techniques for template generation from image content includes extracting information associated with an input image. The information comprises: 1) layout information indicating positions of content corresponding to a content type of a plurality of content types within the input image; and 2) text attributes indicating at least a font of text included in the input image. A user-editable template having the characteristics of the input image is generated based on the layout information and the text attributes.Type: GrantFiled: October 7, 2021Date of Patent: March 21, 2023Assignee: Adobe Inc.Inventors: Vinay Aggarwal, Vishwa Vinay, Rizurekh Saha, Prabhat Mahapatra, Niyati Himanshu Chhaya, Harshit Agrawal, Chloe McConnell, Bhanu Prakash Reddy Guda, Balaji Vasan Srinivasan
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Patent number: 11580307Abstract: A digital attribution system is described to generate predictions of word attributions from subject data, e.g., titles, subject lines of emails, and so on. To do so, an attribution score is first generated by the digital attribution system that describe an amount to which respective words in the subject data cause performance of a corresponding outcome. The attribution scores are then used by the digital attribution system to generate representations for display in a user interface for respective words in the subject data and may also be used to generate attribution recommendations of changes to be made to the subject data.Type: GrantFiled: March 20, 2020Date of Patent: February 14, 2023Assignee: Adobe Inc.Inventors: Niyati Himanshu Chhaya, Sopan Khosla, Balaji Vasan Srinivasan
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Publication number: 20220414135Abstract: Certain embodiments involve using a gated convolutional encoder-decoder framework for applying affective characteristic labels to input text. For example, a method for identifying an affect label of text with a gated convolutional encoder-decoder model includes receiving, at a supervised classification engine, extracted linguistic features of an input text and a latent representation of an input text. The method also includes predicting, by the supervised classification engine, an affect characterization of the input text using the extracted linguistic features and the latent representation. Predicting the affect characterization includes normalizing and concatenating a linguistic feature representation generated from the extracted linguistic features with the latent representation to generate an appended latent representation. The method also includes identifying, by a gated convolutional encoder-decoder model, an affect label of the input text using the predicted affect characterization.Type: ApplicationFiled: August 29, 2022Publication date: December 29, 2022Inventors: Kushal CHAWLA, Niyati Himanshu CHHAYA, Sopan KHOSLA
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Publication number: 20220343189Abstract: Certain embodiments involve using machine-learning methods to generate a recommendation for sequential content items. A method involves accessing a content item associated with an interaction stage in an online environment. A stage graph, which includes a ratio of interactions, of the content item is generated. An additional content item that includes additional stage-transition content is identified. A sequencing function outcome indicating a portion of the ratio of interactions is determined. A transition probability of receiving an interaction with stage-transition content and an additional interaction with the additional stage-transition content is calculated. A content provider system is caused to provide a recipient device with interactive content that includes the additional content item.Type: ApplicationFiled: April 22, 2021Publication date: October 27, 2022Inventors: Niyati Himanshu Chhaya, Niranjan Kumbi, Balaji Vasan Srinivasan, Akangsha Bedmutha, Ajay Awatramani, Sreekanth Reddy
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Patent number: 11475223Abstract: Techniques are disclosed for generating an output sentence from an input sentence by replacing an input tone of the input sentence with a target tone. For example, an input sentence is parsed to separate semantic meaning of the input sentence from the tone of the input sentence. The input tone is indicative of one or more characteristics of the input sentence, such as politeness, formality, humor, anger, etc. in the input sentence, and thus, a measure of the input tone is a measure of such characteristics of the input sentence. An output sentence is generated based on the semantic meaning of the input sentence and a target tone, such that the output sentence and the input sentence have similar semantic meaning, and the output sentence has the target tone that is different from the input tone of the input sentence.Type: GrantFiled: July 30, 2019Date of Patent: October 18, 2022Assignee: Adobe Inc.Inventors: Niyati Himanshu Chhaya, Pranav Ravindra Manerikar, Sopan Khosla
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Patent number: 11449537Abstract: Certain embodiments involve using a gated convolutional encoder-decoder framework for applying affective characteristic labels to input text. For example, a method for identifying an affect label of text with a gated convolutional encoder-decoder model includes receiving, at an encoder, input text. The method also includes encoding the input text to generate a latent representation of the input text. Additionally, the method includes receiving, at a supervised classification engine, extracted linguistic features of the input text and the latent representation of the input text. Further, the method includes predicting an affect characterization of the input text using the extracted linguistic features and the latent representation. Furthermore, the method includes identifying an affect label of the input text using the predicted affect characterization.Type: GrantFiled: December 18, 2018Date of Patent: September 20, 2022Assignee: ADOBE INC.Inventors: Kushal Chawla, Niyati Himanshu Chhaya, Sopan Khosla