Patents by Inventor Meredith Leigh Critzer

Meredith Leigh Critzer 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).

  • Publication number: 20240153490
    Abstract: A system may include processor(s), and memory in communication with the processor(s) and storing instructions configured to cause the system to correct ASR errors. The system may receive a transcription comprising transcribed word(s) and may determine whether the transcribed word(s) exceed associated predefined confidence level(s). Responsive to determining a transcribed word does not exceed a predefined confidence level, the system may generate a predicted word. The system may calculate a distance between numerical representations of the transcribed word and the predicted word and may determine whether the distance exceeds a predefined threshold. Responsive to determining the distance exceeds the predefined threshold, the system may determine whether at least one red flag word of a list of red flag words corresponds to a context of the transcription, and, responsive to making that determination, may classify the transcription as associated with a first category.
    Type: Application
    Filed: January 17, 2024
    Publication date: May 9, 2024
    Inventors: Aysu Ezen Can, Feng Qiu, Guadalupe Bonilla, Meredith Leigh Critzer, Michael Mossoba, Alexander Lin, Tyler Maiman, Mia Rodriguez, Vahid Khanagha, Joshua Edwards
  • Patent number: 11922926
    Abstract: A system may include processor(s), and memory in communication with the processor(s) and storing instructions configured to cause the system to correct ASR errors. The system may receive a transcription comprising transcribed word(s) and may determine whether the transcribed word(s) exceed associated predefined confidence level(s). Responsive to determining a transcribed word does not exceed a predefined confidence level, the system may generate a predicted word. The system may calculate a distance between numerical representations of the transcribed word and the predicted word and may determine whether the distance exceeds a predefined threshold. Responsive to determining the distance exceeds the predefined threshold, the system may determine whether at least one red flag word of a list of red flag words corresponds to a context of the transcription, and, responsive to making that determination, may classify the transcription as associated with a first category.
    Type: Grant
    Filed: September 14, 2021
    Date of Patent: March 5, 2024
    Assignee: CAPITAL ONE SERVICES, LLC
    Inventors: Aysu Ezen Can, Feng Qiu, Guadalupe Bonilla, Meredith Leigh Critzer, Michael Mossoba, Alexander Lin, Tyler Maiman, Mia Rodriguez, Vahid Khanagha, Joshua Edwards
  • Publication number: 20230085433
    Abstract: A system may include processor(s), and memory in communication with the processor(s) and storing instructions configured to cause the system to correct ASR errors. The system may receive a transcription comprising transcribed word(s) and may determine whether the transcribed word(s) exceed associated predefined confidence level(s). Responsive to determining a transcribed word does not exceed a predefined confidence level, the system may generate a predicted word. The system may calculate a distance between numerical representations of the transcribed word and the predicted word and may determine whether the distance exceeds a predefined threshold. Responsive to determining the distance exceeds the predefined threshold, the system may determine whether at least one red flag word of a list of red flag words corresponds to a context of the transcription, and, responsive to making that determination, may classify the transcription as associated with a first category.
    Type: Application
    Filed: September 14, 2021
    Publication date: March 16, 2023
    Inventors: Aysu Ezen Can, Feng Qiu, Guadalupe Bonilla, Meredith Leigh Critzer, Michael Mossoba, Alexander Lin, Tyler Maiman, Mia Rodriguez, Vahid Khanagha, Joshua Edwards