Abstract: The disclosed technology involves autonomously identifying goals and sub-goals from a user utterance and generating responses to the user based on the goals and sub-goals.

Abstract: A method is disclosed. The method comprises receiving data for a virtual private cloud (VPC), receiving, via a graphical user interface (GUI), a request to access the VPC data and displaying, at the GUI, a resource page providing a filter view of VPC resources including in the VPC data.

Abstract: The disclosed technology involves autonomously identifying goals and sub-goals from a user utterance and generating responses to the user based on the goals and sub-goals.

Abstract: Systems and methods for identifying irregularities during an automated user interaction are disclosed. The system may receive a communication and extract a perceived irregularity from the communication. The system may generate a first explanatory hypothesis associated with the perceived irregularity having an associated confidence measurement. The system may selectively retrieve user information based on the generated hypothesis and generate an investigational strategy associated with the hypothesis. In response to the investigational strategy, the system may receive a user communication, and the system may update the confidence measurement based on the user communication. When the confidence measurement exceeds the predetermined confidence threshold the system may validate the perceived irregularity as a true irregularity and provide a computer-generated dialogue response indicative of a proposed resolution of the irregularity.

Abstract: Systems and methods are provided herein for autonomously determining and resolving a customer's perceived discrepancy during a customer service interaction. The method can include receiving an incoming communication from a customer; extracting a perceived state and an expected state (possibly of a product or service) based on the incoming communication; determining a perceived discrepancy between the perceived and expected states of the customer; retrieving customer information; extracting a current state of the customer from the retrieved customer information, verifying, by a rule-based platform, the discrepancy; generating a response based on the discrepancy after comparing the perceived stated with the current state, where the response may include a confirmation or a correction related to the discrepancy and a personalized explanation describing the current state of the customer; and outputting, for presentation to the customer, the response.

Abstract: Systems and methods for identifying irregularities during an automated user interaction are disclosed. The system may receive a communication and extract a perceived irregularity from the communication. The system may generate a first explanatory hypothesis associated with the perceived irregularity having an associated confidence measurement. The system may selectively retrieve user information based on the generated hypothesis and generate an investigational strategy associated with the hypothesis. In response to the investigational strategy, the system may receive a user communication, and the system may update the confidence measurement based on the user communication. When the confidence measurement exceeds the predetermined confidence threshold the system may validate the perceived irregularity as a true irregularity and provide a computer-generated dialogue response indicative of a proposed resolution of the irregularity.

Abstract: The disclosed technology involves autonomously identifying goals and sub-goals from a user utterance and generating responses to the user based on the goals and sub-goals.

Abstract: Systems and methods are provided herein for autonomously determining and resolving a customer's perceived discrepancy during a customer service interaction. The method can include receiving an incoming communication from a customer; extracting a perceived state and an expected state (possibly of a product or service) based on the incoming communication; determining a perceived discrepancy between the perceived and expected states of the customer; retrieving customer information; extracting a current state of the customer from the retrieved customer information, verifying, by a rule-based platform, the discrepancy; generating a response based on the discrepancy after comparing the perceived stated with the current state, where the response may include a confirmation or a correction related to the discrepancy and a personalized explanation describing the current state of the customer; and outputting, for presentation to the customer, the response.

Abstract: Techniques are disclosed for recognizing user personality in accordance with a speech recognition system. For example, a technique for recognizing a personality trait associated with a user interacting with a speech recognition system includes the following steps/operations. One or more decoded spoken utterances of the user are obtained. The one or more decoded spoken utterances are generated by the speech recognition system. The one or more decoded spoken utterances are analyzed to determine one or more linguistic attributes (morphological and syntactic filters) that are associated with the one or more decoded spoken utterances. The personality trait associated with the user is then determined based on the analyzing step/operation.

Abstract: Techniques are disclosed for recognizing user personality in accordance with a speech recognition system. For example, a technique for recognizing a personality trait associated with a user interacting with a speech recognition system includes the following steps/operations. One or more decoded spoken utterances of the user are obtained. The one or more decoded spoken utterances are generated by the speech recognition system. The one or more decoded spoken utterances are analyzed to determine one or more linguistic attributes (morphological and syntactic filters) that are associated with the one or more decoded spoken utterances. The personality trait associated with the user is then determined based on the analyzing step/operation.

Abstract: Techniques are disclosed for recognizing user personality in accordance with a speech recognition system. For example, a technique for recognizing a personality trait associated with a user interacting with a speech recognition system includes the following steps/operations. One or more decoded spoken utterances of the user are obtained. The one or more decoded spoken utterances are generated by the speech recognition system. The one or more decoded spoken utterances are analyzed to determine one or more linguistic attributes (morphological and syntactic filters) that are associated with the one or more decoded spoken utterances. The personality trait associated with the user is then determined based on the analyzing step/operation.

Abstract: Techniques for recognizing a personality trait associated with a user. Input from the user is analyzed to determine a number of words, including a number of compound words. The personality trait associated with the user is determined based, at least in part, on the number of compound words exceeding a threshold.

Abstract: Techniques are disclosed for recognizing user personality in accordance with a speech recognition system. For example, a technique for recognizing a personality trait associated with a user interacting with a speech recognition system includes the following steps/operations. One or more decoded spoken utterances of the user are obtained. The one or more decoded spoken utterances are generated by the speech recognition system. The one or more decoded spoken utterances are analyzed to determine one or more linguistic attributes (morphological and syntactic filters) that are associated with the one or more decoded spoken utterances. The personality trait associated with the user is then determined based on the analyzing step/operation.

Abstract: Techniques are disclosed for recognizing user personality in accordance with a speech recognition system. For example, a technique for recognizing a personality trait associated with a user interacting with a speech recognition system includes the following steps/operations. One or more decoded spoken utterances of the user are obtained. The one or more decoded spoken utterances are generated by the speech recognition system. The one or more decoded spoken utterances are analyzed to determine one or more linguistic attributes (morphological and syntactic filters) that are associated with the one or more decoded spoken utterances. The personality trait associated with the user is then determined based on the analyzing step/operation.