Machine learning models for automated processing of transcription database entries
US11947629B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 1, 2021 |
| Grant date | Apr 2, 2024 |
| Priority date | — |
| Expiry date | Oct 1, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2218/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.