Patent ID: 11967309
Assignee: BANK OF AMERICA CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G  H | IPC G

Claim 0:
1. A method for providing pre-processing of an utterance prior to feeding utterance-related data to a sequential neural network classifier for conversation sentiment scoring, the utterance being expressed, by a user, to an interactive response system during an interaction between the user and the interactive response system, the method comprising:
a conversation manager receiving a stateless application programming interface (“API”) request including the utterance, previous utterance data and a sequence of labels, each label being associated with a previous utterance expressed by a user during the interaction;
a natural language processor processing the utterance to output an utterance intent, a semantic meaning of the utterance and an utterance parameter, the utterance parameter comprising one or more words included in the utterance and being associated with the utterance intent;
a signal extractor processing the utterance, the utterance intent, the semantic meaning, the utterance parameter, and the previous utterance data to generate one or more utterance signals;
an utterance sentiment classifier:
storing a hierarchy of rules, each rule being associated with one or more rule signals and a label;
in response to receiving the one or more utterance signals from the signal extractor, iterating through the hierarchy of rules in sequential order to identify a rule in the hierarchy for which the one or more utterance signals are a superset of the rule's one or more rule signals, the iterating ending when the rule is identified;

the sequential neural network classifier:
receiving a data input including the sequence of labels and a label associated with the rule identified by the utterance sentiment classifier, the data input not including the utterance;
processing the data input using a trained algorithm; and
outputting a sentiment score;

the conversation manager:
analyzing a combination of the utterance intent, the label and the sentiment score for identifying a response to the utterance;
when the label is assigned one of a first subset of labels and the sentiment score is within a pre-determined range, executing an automated rules-based algorithm to identify the response, wherein the automated rules-based algorithm uses the utterance intent to determine the response;
when the label is assigned one of a second subset of labels and the sentiment score is outside the pre-determined range, executing an automated escalated rules-based algorithm to identify the response, wherein the escalated rules-based algorithm uses the label to determine the response;
augmenting the stateless API request to include the response, the utterance intent, the semantic meaning, the utterance parameter, the label and the sentiment score; and
after the augmenting, transmitting the stateless API request to the interactive response system; and
the interactive response system receiving the stateless API request and outputting the response to the user;, wherein:
the pre-processing of the utterance by the natural language processor, the signal extractor and the utterance sentiment classifier reduces the sequential neural network classifier's utterance-related data input to the label and the sequence of labels, thereby increasing a speed at which the sequential neural network classifier returns the sentiment score and decreasing resources consumed by the sequential neural network classifier when processing the data input.