Patent ID: 11948557
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 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, wherein the one or more utterance signals corresponds to a most probable intent of the user;
when the one or more utterance signals has been previously generated during the interaction and has previously not satisfied the user, then modifying the one or more utterance signals to correspond to a next most probable intent of the user; and

an utterance sentiment classifier:
storing a hierarchy of rules, each rule in the hierarchy of rules 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 first rule in the hierarchy for which the one or more utterance signals are a superset of the first rule's one or more rule signals; and

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:
identifying a response to the user utterance based on the utterance intent, the label and the sentiment score;
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 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.