Machine learning models for automated processing of transcription database entries

A computer system comprising:

• memory hardware configured to store a transcription database, a call database, and instructions, wherein the transcription database includes multiple call transcription data entries, and wherein the call database includes multiple agent call log data entries;
• and
• processor hardware configured to execute the instructions, wherein the instructions include:
• joining at least a portion of the call transcription data entries with at least a portion of the agent call log data entries according to timestamps associated with the entries to generate a set of joined call data entries, wherein the set of joined call data entries includes the call transcription data entries paired with respective ones of the agent call log data entries,
• for at least one of the set of joined call data entries:
• generating an input vector, based on the joined call data entry, for an unsupervised machine learning model, and
• for at least a portion of the input vectors:
• supplying the input vector to the unsupervised machine learning model to assign an output topic classification of the model to the joined call data entry associated with the input vector,
• supplying the input vector to at least one sub-topic model associated with the output topic classification to assign one or more sub-topic output classifications to the joined call data entry associated with the input vector, and
• modifying a user interface of a user device to display the output topic classification.