US 11,694,038 B2
Systems and methods for generating dynamic conversational responses through aggregated outputs of machine learning models
Minh Le, McLean, VA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Sep. 23, 2020, as Appl. No. 17/30,059.
Prior Publication US 2022/0092269 A1, Mar. 24, 2022
Int. Cl. G06F 40/35 (2020.01); G06N 3/088 (2023.01); G06N 3/045 (2023.01)
CPC G06F 40/35 (2020.01) [G06N 3/045 (2023.01); G06N 3/088 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for generating dynamic conversational responses through aggregated outputs of machine learning models, the system comprising:
storage circuitry configured to store:
a first machine learning model, wherein the first machine learning model is trained using a multi-class cross entropy loss function; and
a second machine learning model, wherein the second machine learning model is trained using a binary cross entropy loss function;
control circuitry configured to:
receive a first user action during a conversational interaction with a user interface;
determine, based on the first user action, a first feature input for the first machine learning model;
determine, based on the first user action, a second feature input for the second machine learning model;
input the first feature input into the first machine learning model to generate a first output from the first machine learning model;
input the first feature input into the second machine learning model to generate a second output from the second machine learning model;
determine a third output based on a weighted average of the first output and the second output; and
select a subset of the dynamic conversational responses from a plurality of dynamic conversational responses based on the third output; and
input/output circuitry configured to:
generate, at the user interface, the subset of the dynamic conversational responses during the conversational interaction.