Invention Grant
- Patent Title: Machine learning models for automated processing of transcription database entries
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Application No.: US17464213Application Date: 2021-09-01
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Publication No.: US11947629B2Publication Date: 2024-04-02
- Inventor: Akash Dwivedi , Christopher R. Markson , Pritesh J. Shah
- Applicant: Evernorth Strategic Development, Inc.
- Applicant Address: US MO St. Louis
- Assignee: Evernorth Strategic Development, Inc.
- Current Assignee: Evernorth Strategic Development, Inc.
- Current Assignee Address: US MO St. Louis
- Agency: Miller Johnson
- Main IPC: G06F18/214
- IPC: G06F18/214 ; G06F16/383 ; G06F40/295 ; G10L15/26

Abstract:
A computer system includes processor hardware configured to execute instructions that include joining at least a portion of multiple call transcription data entries with at least a portion of multiple agent call log data entries according to timestamps associated with the entries to generate a set of joined call data entries, and validating the joined call data entry by determining whether a transcribed entity name matches with entity identifier information associated with the agent call log data entry. The instructions include preprocessing the joined call data entry according to word confidence score data entries associated with the call transcription data entry to generate preprocessed text, performing natural language processing vectorization on the preprocessed text to generate an input vector, and supplying the input vector to an unsupervised machine learning model to assign an output topic classification of the model to the joined call data entry associated with the input vector.
Public/Granted literature
- US20230068878A1 MACHINE LEARNING MODELS FOR AUTOMATED PROCESSING OF TRANSCRIPTION DATABASE ENTRIES Public/Granted day:2023-03-02
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