Patents by Inventor Greg Langmead

Greg Langmead 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).

  • Adapter for allowing both online and offline training of a text to text system
    Patent number: 7624020
    Abstract: An adapter for a text to text training. A main corpus is used for training, and a domain specific corpus is used to adapt the main corpus according to the training information in the domain specific corpus. The adaptation is carried out using a technique that may be faster than the main training. The parameter set from the main training is adapted using the domain specific part.
    Type: Grant
    Filed: September 9, 2005
    Date of Patent: November 24, 2009
    Assignee: Language Weaver, Inc.
    Inventors: Kenji Yamada, Kevin Knight, Greg Langmead
  • Task parallelization in a text-to-text system
    Patent number: 7389222
    Abstract: Parallelization of word alignment for a text-to-text operation. The training data is divided into multiple groups, and training is carried out of each group on separate processors. Different techniques can be carried out to increase the speed of the processing. The hookups can be done only once for all of multiple different iterations. Moreover, parallel operations can apply only to the counts, since this may be the most time-consuming part.
    Type: Grant
    Filed: April 26, 2006
    Date of Patent: June 17, 2008
    Assignee: Language Weaver, Inc.
    Inventors: Greg Langmead, Kenji Yamada, Kevin Knight, Daniel Marcu
  • Adapter for allowing both online and offline training of a text to text system
    Publication number: 20070094169
    Abstract: An adapter for a text to text training. A main corpus is used for training, and a domain specific corpus is used to adapt the main corpus according to the training information in the domain specific corpus. The adaptation is carried out using a technique that may be faster than the main training. The parameter set from the main training is adapted using the domain specific part.
    Type: Application
    Filed: September 9, 2005
    Publication date: April 26, 2007
    Inventors: Kenji Yamada, Kevin Knight, Greg Langmead