US 12,223,423 B2
Systems and methods for generating automated natural language responses based on identified goals and sub-goals from an utterance
Alexandra Coman, Tysons Corner, VA (US); Zachary Kulis, Arlington, VA (US); Rui Zhang, New York, NY (US); Liwei Dai, Oakton, VA (US); Erik T. Mueller, Chevy Chase, MD (US); and Vinay Igure, Ashburn, VA (US)
Assigned to CAPITAL ONE SERVICES, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Oct. 2, 2020, as Appl. No. 17/062,241.
Prior Publication US 2022/0108164 A1, Apr. 7, 2022
Int. Cl. G10L 15/22 (2006.01); G06F 40/56 (2020.01); G06N 3/08 (2023.01)
CPC G06N 3/08 (2013.01) [G06F 40/56 (2020.01); G10L 15/22 (2013.01); G10L 2015/223 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
one or more processors;
a natural language processing (NLP) device; and
a memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the system to:
continuously receive one or more communications from a user;
iteratively update one or more programming commands to generate one or more updated programming commands;
dynamically and autonomously, via the NLP device:
interpret the one or more communications;
responsive to interpreting the one or more communications, generate one or more solutions; and
based on the one or more updated programming commands, revise the one or more solutions to generate one or more updated solutions;
retrieve a list of goals from a domain database;
identify, using a rule-based approach, a first goal and a first sub-goal in the one or more communications based on the list of goals;
transform, using the rule-based approach, the one or more communications based on the list of goals to generate one or more normalized communications;
determine whether the list of goals comprises the first goal and the first sub-goal;
when the list of goals comprises the first goal and the first sub-goal, determine, using a machine learning model, whether the first sub-goal corresponds to the first goal based on the list of goals; and
when the list of goals comprises the first goal and the first sub-goal and the first sub-goal corresponds to the first goal:
determine whether the domain database comprises at least one solution plan for the first goal that does not involve the first sub-goal or whether the at least one solution plan can be generated; and
when the domain database comprises the at least one solution plan for the first goal that does not involve the first sub-goal or the at least one solution plan can be generated:
determine, using the machine learning model, whether the one or more normalized communications comprise an expression of preference for the first sub-goal; and
when the one or more normalized communications comprise the expression of preference for the first sub-goal:
 generate a first recommended solution based on the one or more updated solutions by selecting a solution plan from the at least one solution plan in the domain database or by generating the at least one solution plan;
 determine whether the first recommended solution involves the first sub-goal;
 when the first recommended solution does not involve the first sub-goal, provide the first recommended solution to the user with a first explanation explaining why the first sub-goal was excluded; and
 when the first recommended solution involves the first sub-goal, provide the first recommended solution to the user.