A method, computer system, and a computer program product for automated urgency detection is provided. The present invention may include capturing at least one caller parameter. The present invention may include determining whether an incoming call is urgent. The present invention may include conveying a determined urgency to a receiver of the incoming call.

The present invention relates to device, system and method for determining a priority level and/or conversation duration of a call. An improved and adaptive device comprises a signal input (31) for obtaining an image data signal (21) of a user initiating a call, a physiological data extraction unit (32) for extracting physiological data (22) of the user from the obtained image data signal (21), a health condition determination unit (33) for determining the health condition (23) of the user based on the extracted physiological data, and a prioritization unit (34) for determining the priority level and/or conversation duration (24) of the call based on the determined health condition of the user.

Systems and methods to process and/or present information relating to voice messages for a user that are received from other persons. In one embodiment, a method implemented in a data processing system includes: receiving first data associated with prior communications or activities for a first user on a mobile device; receiving a voice message for the first user; transcribing the voice message using the first data to provide a transcribed message; and sending the transcribed message to the mobile device for display to the user.

A system and method provide an integrated automation solution that links multiple systems and applications of a contact center operation and provides a unified support interface and unified knowledge base that delivers relevant data in real-time to assist contact center personnel during a customer interaction. Robotic Process Automation (RPA) is used for automating workflows and processes with robots (e.g., attended and/or unattended) that perform various tasks and activities for capturing information (data, documents, etc.) from multiple front-end and/or back-end systems and applications to provide the necessary data and information in real-time during a contact center session.

In one embodiment, the techniques herein are directed to conveying a reason for a call from a user device. For instance, an illustrative method herein may comprise: determining, by a user device, a second device to participate in a call with a user of the user device and a reason for the call; transmitting, from the user device, a message to an intermediate service to inform the intermediate service about the second device, the user, and the reason for the call, wherein the intermediate service conveys the user and the reason for the call to the second device; and receiving, at the user device, the call initiated by the second device, wherein the second device is aware of the user and the reason for the call prior to initiating the call.

According to one example, a method includes facilitating communication between a user web application and an entity. The method may be performed by a communication server of a web communication service. The method includes receiving a request from the user web application to communicate with the entity, establishing a communication session between the user web application and an automated agent, obtaining contextual information associated with the communication session, the contextual information including information provided by the user web application, determining that a user of the user web application should be connected with a live agent, and in response to the determining, connecting the user web application with a terminal of an agent associated with the entity. The method further includes providing the live agent associated with the entity with the contextual information.

A method, computer system, and a computer program product for automated urgency detection is provided. The present invention may include capturing at least one caller parameter. The present invention may include determining whether an incoming call is urgent. The present invention may include conveying a determined urgency to a receiver of the incoming call.

In a method of using structured communications in an observation platform with cloud computing, a signal from a first communication device is received by a second communication device associated with a first computer system. The second computer system forwards the signal from the first computer system to a second computer system, wherein the second computer system is physically remote from the first computer system and connected with the first computer system via a network. The second computer system derives context information for the signal, the deriving based on a plurality of factors derived from an analysis of the signal, wherein the plurality of factors comprises a speech to text analysis of the signal, and wherein the second computer system is cloud based. The second computer system determines at least one destination for the signal based on the plurality of factors for the context information.

A system and method of verifying a caller identification utilizing a server that communicates with a computing device capable of monitoring communication networks for specific communications from an enterprise voice network. The server can push a spoof prevention contact list to user devices. Additionally, the server can receive notifications from the computing device in response to user inputs that allow match analysis to occur with the information in the received notifications. When a match is found, the server can send a notification to a user device to modify a contact name in the spoof prevention list stored in the user device. After a specified time, the contact name can be altered back to the original state. As an example, the contact name in the spoof prevention list may start out as “unverified call,” and be changed temporarily to “verified call” upon receipt of the notification.

A communication system for processing a call includes control logic and at least one machine learning model generating call classifiers from outputs of an audio signal processor and a natural language processor operated on the call. Heuristic logic transforms the call classifiers into weighted sub-metrics for the call, and aggregate normalized Gaussian logic transforms the weighted sub-metrics into a metric control that may be applied as a feedback signal to adapt the operation of the control logic. The control logic in turn may adapt the behavior of an agent, automated voice attendant, or a template utilized in a call flow.