| CPC G06Q 10/06398 (2013.01) [G06F 9/451 (2018.02); G06F 40/284 (2020.01); G06F 40/295 (2020.01); G10L 17/22 (2013.01)] | 19 Claims |
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13. A method, comprising:
training at least one machine learning model to detect signals, wherein the at least one machine learning model includes a machine learning model that is trained with training data comprising text that is annotated with correct question classifications;
using the at least one machine learning model to detect a plurality of signals associated with an interaction among two or more speaker roles, wherein a signal comprises a text-based signal or an audio-based signal within a respective audio or text stream associated with the two or more speaker roles;
combining, using one or more processors, two or more signals of the plurality of signals using a prescribed set of operators into a combined signal, wherein the prescribed set of operators are defined by a set of interaction processing configuration information;
determining a recommended event evaluation result based at least in part on whether a criterion associated with an event has been met with respect to the interaction based at least in part on the combined signal;
outputting, at a user interface:
one or more of audio portions and text portions of the interaction corresponding to the two or more signals that were detected from the interaction and that were combined into the combined signal; and
the recommended event evaluation result corresponding to the event; and
receiving a user feedback comprising a correction to the recommended event evaluation result corresponding to the event; and
retraining the at least one machine learning model based at least in part on the correction to improve subsequent signal detection from subsequent interactions.
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