Patents by Inventor Bakhtiyar Hussain Syed

Bakhtiyar Hussain Syed 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).

  • Patent number: 11900056
    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.
    Type: Grant
    Filed: February 21, 2023
    Date of Patent: February 13, 2024
    Assignee: Adobe Inc.
    Inventors: Balaji Vasan Srinivasan, Gaurav Verma, Bakhtiyar Hussain Syed, Anandhavelu Natarajan
  • Publication number: 20230196014
    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.
    Type: Application
    Filed: February 21, 2023
    Publication date: June 22, 2023
    Applicant: Adobe Inc.
    Inventors: Balaji Vasan Srinivasan, Gaurav Verma, Bakhtiyar Hussain Syed, Anandhavelu Natarajan
  • Patent number: 11636264
    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.
    Type: Grant
    Filed: September 7, 2021
    Date of Patent: April 25, 2023
    Assignee: Adobe Inc.
    Inventors: Balaji Vasan Srinivasan, Gaurav Verma, Bakhtiyar Hussain Syed, Anandhavelu Natarajan
  • Publication number: 20210406465
    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.
    Type: Application
    Filed: September 7, 2021
    Publication date: December 30, 2021
    Applicant: Adobe Inc.
    Inventors: Balaji Vasan Srinivasan, Gaurav Verma, Bakhtiyar Hussain Syed, Anandhavelu Natarajan
  • Patent number: 11157693
    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.
    Type: Grant
    Filed: February 25, 2020
    Date of Patent: October 26, 2021
    Assignee: Adobe Inc.
    Inventors: Balaji Vasan Srinivasan, Gaurav Verma, Bakhtiyar Hussain Syed, Anandhavelu Natarajan
  • Publication number: 20210264109
    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.
    Type: Application
    Filed: February 25, 2020
    Publication date: August 26, 2021
    Applicant: Adobe Inc.
    Inventors: Balaji Vasan Srinivasan, Gaurav Verma, Bakhtiyar Hussain Syed, Anandhavelu Natarajan