Patent ID: 11935532
Assignee: BANK OF AMERICA CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G  H | IPC G

Claim 18:
19. A method for processing a user 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, said method being performed on at least one of a plurality of distributed servers, said method comprising:
receiving, using a first processor associated with a conversation manager, a stateless application programming interface (“API”) request, the API request for storing, in a configurable memory, the utterance, previous utterance data and a sequence of labels, each label in the sequence of labels being associated with a previous utterance expressed by a user during the interaction, said previous utterance data being limited to a pre-determined number of utterances occurring immediately prior to the utterance;
processing the utterance, using a natural language processor in electronic communication with the first processor, 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, the natural language processor further configured to append the utterance intent, the semantic meaning of the utterance and the utterance parameter to the API request;
processing, using a signal extractor processor, the utterance, the utterance intent, the semantic meaning, the utterance parameter, and the previous utterance data extracted from the API request to generate a plurality of utterance signals, wherein the signal extractor processor is configured to append the plurality of utterance signals to the API request;
using an utterance sentiment classifier to:
store a hierarchy of rules in a memory, each rule in the hierarchy of rules being associated with one or more rule signals and a label;
use a second processor to, in response to receiving the one or more utterance signals from the signal extractor processor, iterate through the hierarchy of rules to identify a first rule in the hierarchy for which the one or more utterance signals is a superset of the first rule's one or more rule signals;
append, using the second processor, to the sequence of labels stored in the API request, a label associated with the first rule;

using a sequential neural network classifier:
receive a data input including the sequence of labels and the label associated with the first rule, the data input not including the utterance;
process the data input using a trained algorithm; and
based on the processing, append a sentiment score to the API request, said sentiment score being associated, within the API request, to the utterance;

using the first processor to:
identify, a response to the user utterance based on the utterance intent, the label and the sentiment score;
append, the response to the API request; and
after the appending, transmit the API request to the interactive response system; and

receiving, using the interactive response system, the API request and outputting the response included therein to the user;
wherein:
the pre-processing of the utterance by the natural language processor, the signal extractor processor 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.