Patents by Inventor Bryan Rieger

Bryan Rieger 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: 10348896
    Abstract: A facility and method for analyzing and classifying calls without transcription. The facility analyzes individual frames of an audio to identify speech and measure the amount of time spent in speech for each channel (e.g., caller channel, agent channel). Additional telephony metrics such as R-factor or MOS score and other metadata may be factored in as audio analysis inputs. The facility then analyzes the frames together as a whole and formulates a clustered-frame representation of a conversation to further identify dialog patterns and characterize call classification. Based on the data in the clustered-frame representation, the facility is able to make estimations of call classification. The correlation of dialog patterns to call classification may be utilized to develop targeted solutions for call classification issues, target certain advertising channels over others, evaluate advertising placements at scale, score callers, and to identify spammers.
    Type: Grant
    Filed: March 31, 2017
    Date of Patent: July 9, 2019
    Assignee: Marchex, Inc.
    Inventors: Chris Kolbegger, Jason Flaks, Tim Graber, Bryan Rieger, Ziad Ismail, Govindaraj Ramanathan, Darren Spehr, Matthew Berk
  • Patent number: 10230851
    Abstract: A system and method for monitoring telephone calls to detect call traffic pumping activity and take corrective action is described. The system receives a group of training telephone calls having associated call audio content and associated information, and the system analyzes the training telephone calls to generate and store a classification model that correlates call features and associations with a probability of call traffic pumping activity. The system receives a subsequent monitored telephone call to be analyzed. The system analyzes the monitored telephone call to identify features present in the audio content of the monitored telephone call and other associated information. The system then compares the features and associated information to the stored classification model in order to determine a probability that the monitored telephone call is associated with call traffic pumping activity.
    Type: Grant
    Filed: October 31, 2016
    Date of Patent: March 12, 2019
    Assignee: Marchex, Inc.
    Inventors: Jason Flaks, Iroro Orife, Bryan Rieger, Ryan O Rourke, Shane Walker
  • Publication number: 20170366668
    Abstract: A facility and method for analyzing and classifying calls without transcription. The facility analyzes individual frames of an audio to identify speech and measure the amount of time spent in speech for each channel (e.g., caller channel, agent channel). Additional telephony metrics such as R-factor or MOS score and other metadata may be factored in as audio analysis inputs. The facility then analyzes the frames together as a whole and formulates a clustered-frame representation of a conversation to further identify dialogue patterns and characterize call classification. Based on the data in the clustered-frame representation, the facility is able to make estimations of call classification. The correlation of dialogue patterns to call classification may be utilized to develop targeted solutions for call classification issues, target certain advertising channels over others, evaluate advertising placements at scale, score callers, and to identify spammers.
    Type: Application
    Filed: March 31, 2017
    Publication date: December 21, 2017
    Inventors: Chris Kolbegger, Jason Flaks, Tim Graber, Bryan Rieger, Ziad Ismail, Govindaraj Ramanathan, Darren Spehr, Matthew Berk
  • Publication number: 20170149984
    Abstract: A system and method for monitoring telephone calls to detect call traffic pumping activity and take corrective action is described. The system receives a group of training telephone calls having associated call audio content and associated information, and the system analyzes the training telephone calls to generate and store a classification model that correlates call features and associations with a probability of call traffic pumping activity. The system receives a subsequent monitored telephone call to be analyzed. The system analyzes the monitored telephone call to identify features present in the audio content of the monitored telephone call and other associated information. The system then compares the features and associated information to the stored classification model in order to determine a probability that the monitored telephone call is associated with call traffic pumping activity.
    Type: Application
    Filed: October 31, 2016
    Publication date: May 25, 2017
    Inventors: Jason Flaks, Iroro Orife, Bryan Rieger, Ryan O Rourke, Shane Walker
  • Patent number: 9614962
    Abstract: A facility and method for analyzing and classifying calls without transcription. The facility analyzes individual frames of an audio to identify speech and measure the amount of time spent in speech for each channel (e.g., caller channel, agent channel). Additional telephony metrics such as R-factor or MOS score and other metadata may be factored in as audio analysis inputs. The facility then analyzes the frames together as a whole and formulates a clustered-frame representation of a conversation to further identify dialog patterns and characterize call classification. Based on the data in the clustered-frame representation, the facility is able to make estimations of call classification. The correlation of dialog patterns to call classification may be utilized to develop targeted solutions for call classification issues, target certain advertising channels over others, evaluate advertising placements at scale, score callers, and to identify spammers.
    Type: Grant
    Filed: August 24, 2015
    Date of Patent: April 4, 2017
    Assignee: Marchex, Inc.
    Inventors: Chris Kolbegger, Jason Flaks, Tim Graber, Bryan Rieger, Ziad Ismail, Govindaraj Ramanathan, Darren Spehr, Matthew Berk
  • Publication number: 20160330317
    Abstract: A system and method for monitoring telephone calls to detect call traffic pumping activity and take corrective action is described. The system receives a group of training telephone calls having associated call audio content and associated information, and the system analyzes the training telephone calls to generate and store a classification model that correlates call features and associations with a probability of call traffic pumping activity. The system receives a subsequent monitored telephone call to be analyzed. The system analyzes the monitored telephone call to identify features present in the audio content of the monitored telephone call and other associated information. The system then compares the features and associated information to the stored classification model in order to determine a probability that the monitored telephone call is associated with call traffic pumping activity.
    Type: Application
    Filed: May 26, 2015
    Publication date: November 10, 2016
    Inventors: Jason Flaks, Iroro Orife, Bryan Rieger, Ryan O'Rourke, Shane Walker
  • Patent number: 9485354
    Abstract: A system and method for monitoring telephone calls to detect call traffic pumping activity and take corrective action is described. The system receives a group of training telephone calls having associated call audio content and associated information, and the system analyzes the training telephone calls to generate and store a classification model that correlates call features and associations with a probability of call traffic pumping activity. The system receives a subsequent monitored telephone call to be analyzed. The system analyzes the monitored telephone call to identify features present in the audio content of the monitored telephone call and other associated information. The system then compares the features and associated information to the stored classification model in order to determine a probability that the monitored telephone call is associated with call traffic pumping activity.
    Type: Grant
    Filed: May 26, 2015
    Date of Patent: November 1, 2016
    Assignee: Marchex, Inc.
    Inventors: Jason Flaks, Iroro Orife, Bryan Rieger, Ryan O'Rourke, Shane Walker
  • Publication number: 20150365530
    Abstract: A facility and method for analyzing and classifying calls without transcription. The facility analyzes individual frames of an audio to identify speech and measure the amount of time spent in speech for each channel (e.g., caller channel, agent channel). Additional telephony metrics such as R-factor or MOS score and other metadata may be factored in as audio analysis inputs. The facility then analyzes the frames together as a whole and formulates a clustered-frame representation of a conversation to further identify dialogue patterns and characterize call classification. Based on the data in the clustered-frame representation, the facility is able to make estimations of call classification. The correlation of dialogue patterns to call classification may be utilized to develop targeted solutions for call classification issues, target certain advertising channels over others, evaluate advertising placements at scale, score callers, and to identify spammers.
    Type: Application
    Filed: August 24, 2015
    Publication date: December 17, 2015
    Inventors: Chris Kolbegger, Jason Flaks, Tim Graber, Bryan Rieger, Ziad Ismail, Govindaraj Ramanathan, Darren Spehr, Matthew Berk
  • Patent number: 9118751
    Abstract: A facility and method for analyzing and classifying calls without transcription. The facility analyzes individual frames of an audio to identify speech and measure the amount of time spent in speech for each channel (e.g., caller channel, agent channel). Additional telephony metrics such as R-factor or MOS score and other metadata may be factored in as audio analysis inputs. The facility then analyzes the frames together as a whole and formulates a clustered-frame representation of a conversation to further identify dialogue patterns and characterize call classification. Based on the data in the clustered-frame representation, the facility is able to make estimations of call classification. The correlation of dialogue patterns to call classification may be utilized to develop targeted solutions for call classification issues, target certain advertising channels over others, evaluate advertising placements at scale, score callers, and to identify spammers.
    Type: Grant
    Filed: March 15, 2013
    Date of Patent: August 25, 2015
    Assignee: Marchex, Inc.
    Inventors: Chris Kolbegger, Jason Flaks, Tim Graber, Bryan Rieger, Ziad Ismail, Govindaraj Ramanathan, Darren Spehr, Matthew Berk
  • Publication number: 20140270114
    Abstract: A facility and method for analyzing and classifying calls without transcription. The facility analyzes individual frames of an audio to identify speech and measure the amount of time spent in speech for each channel (e.g., caller channel, agent channel). Additional telephony metrics such as R-factor or MOS score and other metadata may be factored in as audio analysis inputs. The facility then analyzes the frames together as a whole and formulates a clustered-frame representation of a conversation to further identify dialogue patterns and characterize call classification. Based on the data in the clustered-frame representation, the facility is able to make estimations of call classification. The correlation of dialogue patterns to call classification may be utilized to develop targeted solutions for call classification issues, target certain advertising channels over others, evaluate advertising placements at scale, score callers, and to identify spammers.
    Type: Application
    Filed: March 15, 2013
    Publication date: September 18, 2014
    Applicant: MARCHEX, INC.
    Inventors: Chris Kolbegger, Jason Flaks, Tim Graber, Bryan Rieger, Ziad Ismail, Govindaraj Ramanathan, Darren Spehr, Matthew Berk