Natural language processing for optimized extractive summarization

An apparatus for generating an optimal extractive summary of a multi-party interaction transcript comprising a plurality of interaction utterances using natural language processing, the apparatus comprising at least one processor and at least one memory including program code, the at least one memory and the program code configured to, with the processor, cause the apparatus to at least:

• identify one or more per-party utterance subsets in the multi-party call transcript, wherein each per-party utterance subset of the one or more per-party utterances comprises a related subset of the plurality of interaction utterances that is associated with an interaction party of a plurality of interaction parties;
• generate a plurality of eligible extractive summaries, wherein:
• (i) each eligible extractive summary of the plurality of eligible comprises a covered subset of the plurality of interaction utterances that complies with one or more optimization constraints, and (ii) the one or more optimization constraints comprises a similarity-based optimization constraint requiring that, if the covered subset for a particular eligible extractive summary of the plurality of extractive summaries comprises a particular interaction utterance of the plurality of interaction utterances that is in a particular per-party utterance subset of the one or more per-party utterances subsets, then the covered subset for the particular eligible extractive summary should further comprise each other interaction utterance of the plurality of interaction utterances that is in any per-party utterance subset of the one or more per-party utterances subsets other than the particular per-party utterance subset and that has a threshold-satisfying utterance similarity measure with respect to the particular interaction utterance;
• for each eligible extractive summary of the plurality of eligible extractive summaries, determine an overall summary utility measure;
• generate the optimal extractive summary based at least in part on each overall summary utility measure for an eligible extractive summary of the plurality of eligible extractive summaries;
• and
• perform one or more summary-based actions based at least in part on the optimal extractive summary.

A computer program product for generating an optimal extractive summary of a multi-party interaction transcript comprising a plurality of interaction utterances using natural language processing, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions configured to:

• identify an input document object;
• process the input document object using a trained convolutional neural document conversion machine learning model to generate a converted document object, wherein:
• (i) the trained convolutional neural document conversion machine learning model is configured to map the input document object to an ordered character combination;
• (ii) the ordered character combination is determined based at least in part on a set of candidate characters;
• (iii) the set of candidate characters include a set of alphanumeric characters and a set of selection indicator characters;
• (iv) the trained convolutional neural document conversion machine learning model is associated with a preprocessing block having a plurality of preprocessing subblocks, one or more main processing blocks each having a plurality of main processing subblocks, and a plurality of postprocessing subblocks each having one or more postprocessing subblocks;
• and (v) the trained convolutional neural document conversion machine learning model is associated with a preprocessing subblock repetition count hyper-parameter that defines a preprocessing subblock count of the plurality of preprocessing subblocks;
• and
• perform one or more prediction-based actions based at least in part on the converted document object.