US 11,989,514 B2
Identifying high effort statements for call center summaries
Aysu Ezen Can, Cary, NC (US); Zachary S. Brown, Midlothian, VA (US); and Chris Symons, Hilton, NY (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Mar. 18, 2022, as Appl. No. 17/698,018.
Prior Publication US 2023/0297778 A1, Sep. 21, 2023
Int. Cl. G06F 40/30 (2020.01); G06F 40/166 (2020.01); G06F 40/284 (2020.01); G10L 15/06 (2013.01); G10L 15/16 (2006.01); G10L 15/22 (2006.01); H04M 3/42 (2006.01); H04M 3/51 (2006.01)
CPC G06F 40/284 (2020.01) [G06F 40/166 (2020.01); G10L 15/063 (2013.01); G10L 15/16 (2013.01); G10L 15/22 (2013.01); H04M 3/42221 (2013.01); H04M 3/5175 (2013.01); G06F 40/30 (2020.01); H04M 2201/40 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for ranking utterances in a natural language processing environment, the system comprising:
a speech recognizer configured to:
receive an interactive communication between a first participant and a second participant;
extract individual utterances of the first participant; and
convert the individual utterances to a textual transcript of individual utterances of the first participant;
a machine learning engine configured to:
evaluate the textual transcript of individual utterances of the first participant, using a customer effort classifier, to determine a binary effort level label for a plurality of the individual utterances of the first participant;
evaluate the textual transcript of individual utterances of the first participant, using the customer effort classifier, to generate attention scores for the plurality of the individual utterances of the first participant, wherein the attention scores are based at least partially on a calculated importance of the individual utterances relative to the plurality of the individual utterances of the first participant;
and
an interactive communication summarizer configured to:
rank the plurality of the individual utterances of the first participant based on the binary effort level label and the attention scores;
select, based on the ranking, one or more utterances of the plurality of the individual utterances of the first participant; and
generate a summary of the interactive communication with the selected one or more utterances.