Patents by Inventor Salman Quazi

Salman Quazi 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).

  • Incorporating an exogenous large-vocabulary model into rule-based speech recognition
    Patent number: 10311878
    Abstract: Incorporation of an exogenous large-vocabulary model into rule-based speech recognition is provided. An audio stream is received by a local small-vocabulary rule-based speech recognition system (SVSRS), and is streamed to a large-vocabulary statistically-modeled speech recognition system (LVSRS). The SVSRS and LVSRS perform recognitions of the audio. If a portion of the audio is not recognized by the SVSRS, a rule is triggered that inserts a mark-up in the recognition result. The recognition result is sent to the LVSRS. If a mark-up is detected, recognition of a specified portion of the audio is performed. The LVSRS result is unified with the SVSRS result and sent as a hybrid response back to the SVSRS. If the hybrid-recognition rule is not triggered, an arbitration algorithm is evoked to determine whether the SVSRS or the LVSRS recognition has a lesser word error rate. The determined recognition is sent as a response to the SVSRS.
    Type: Grant
    Filed: February 7, 2017
    Date of Patent: June 4, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Travis Wilson, Salman Quazi, John Vicondoa, Pradip Fatehpuria
  • INCORPORATING AN EXOGENOUS LARGE-VOCABULARY MODEL INTO RULE-BASED SPEECH RECOGNITION
    Publication number: 20170162204
    Abstract: Incorporation of an exogenous large-vocabulary model into rule-based speech recognition is provided. An audio stream is received by a local small-vocabulary rule-based speech recognition system (SVSRS), and is streamed to a large-vocabulary statistically-modeled speech recognition system (LVSRS). The SVSRS and LVSRS perform recognitions of the audio. If a portion of the audio is not recognized by the SVSRS, a rule is triggered that inserts a mark-up in the recognition result. The recognition result is sent to the LVSRS. If a mark-up is detected, recognition of a specified portion of the audio is performed. The LVSRS result is unified with the SVSRS result and sent as a hybrid response back to the SVSRS. If the hybrid-recognition rule is not triggered, an arbitration algorithm is evoked to determine whether the SVSRS or the LVSRS recognition has a lesser word error rate. The determined recognition is sent as a response to the SVSRS.
    Type: Application
    Filed: February 7, 2017
    Publication date: June 8, 2017
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Travis Wilson, Salman Quazi, John Vicondoa, Pradip Fatehpuria
  • Incorporating an exogenous large-vocabulary model into rule-based speech recognition
    Patent number: 9601108
    Abstract: Incorporation of an exogenous large-vocabulary model into rule-based speech recognition is provided. An audio stream is received by a local small-vocabulary rule-based speech recognition system (SVSRS), and is streamed to a large-vocabulary statistically-modeled speech recognition system (LVSRS). The SVSRS and LVSRS perform recognitions of the audio. If a portion of the audio is not recognized by the SVSRS, a rule is triggered that inserts a mark-up in the recognition result. The recognition result is sent to the LVSRS. If a mark-up is detected, recognition of a specified portion of the audio is performed. The LVSRS result is unified with the SVSRS result and sent as a hybrid response back to the SVSRS. If the hybrid-recognition rule is not triggered, an arbitration algorithm is evoked to determine whether the SVSRS or the LVSRS recognition has a lesser word error rate. The determined recognition is sent as a response to the SVSRS.
    Type: Grant
    Filed: January 17, 2014
    Date of Patent: March 21, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Travis Wilson, Salman Quazi, John Vicondoa, Pradip Fatehpuria
  • Incorporating an Exogenous Large-Vocabulary Model into Rule-Based Speech Recognition
    Publication number: 20150206528
    Abstract: Incorporation of an exogenous large-vocabulary model into rule-based speech recognition is provided. An audio stream is received by a local small-vocabulary rule-based speech recognition system (SVSRS), and is streamed to a large-vocabulary statistically-modeled speech recognition system (LVSRS). The SVSRS and LVSRS perform recognitions of the audio. If a portion of the audio is not recognized by the SVSRS, a rule is triggered that inserts a mark-up in the recognition result. The recognition result is sent to the LVSRS. If a mark-up is detected, recognition of a specified portion of the audio is performed. The LVSRS result is unified with the SVSRS result and sent as a hybrid response back to the SVSRS. If the hybrid-recognition rule is not triggered, an arbitration algorithm is evoked to determine whether the SVSRS or the LVSRS recognition has a lesser word error rate. The determined recognition is sent as a response to the SVSRS.
    Type: Application
    Filed: January 17, 2014
    Publication date: July 23, 2015
    Applicant: MICROSOFT CORPORATION
    Inventors: Travis Wilson, Salman Quazi, John Vicondoa, Pradip Fatehpuria