A system and method for secure storage and management of transitory data, comprising at least a profile manager, a callback manager, a context analysis engine, and a vault manager, which allows a user to create a data container to store data preferences, which encrypts the data stored within a data container, which creates a password for accessing the data container, which temporarily stores the data container, which manages data container interactions between the system user and a second user, such as a business enterprise, and which establishes default preferences and creates a default container based upon context content data.

A method of providing a call service includes: receiving a current location of a first terminal from the first terminal; acquiring information on a time at which the current location is received; acquiring the degree of demand of a vehicle call around the current location; determining whether a call pattern of a user corresponding to the first terminal is stored; determining a vehicle call UI displayed in the first terminal according to the current location, the time, a degree of demand, and existence/non-existence of the call pattern of the user corresponding to the first terminal; and transmitting information about the vehicle call UI to the first terminal.

Machine learning technology can analyze in real-time the data from a call between a person and a customer service representative. Based on this analysis, a server can determine a sentiment score that describes a sentiment expressed by the person or the customer service representative. If the server determines that the sentiment score is less than or equal to a pre-determined value, the server can inform the customer service representative's manager so that the manager can take further action to help the person and/or the customer service representative.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automatically generating enhanced caller identification data are disclosed. In one aspect, a method includes the actions of receiving telephone call placement data that indicates the placement of a telephone call from a calling party to a called party. The actions further include receiving caller identification data. The actions further include accessing first telephone call data that reflects characteristics of telephone calls placed and received by the calling party. The actions further include based on the first telephone call data and the identity of the calling party, determining additional data to combine with the caller identification data. The actions further include generating enhanced caller identification data by combining the additional data with the caller identification data. The actions further include providing, for output, the enhanced caller identification data and data indicating the telephone call.

The rescue priority determination device comprises a driving condition information obtainer, a location information obtainer, and a rescue priority determinator. The driving condition information obtainer and the location information obtainer respectively are configured to obtain driving condition information and location information of a vehicle that made an emergency call, and the rescue priority determinator comprises one or more processors that is configured to determine the rescue priority level for the vehicle that made the emergency call based on the driving condition information and the location information. The rescue priority determinator determines that the need for rescue for the vehicle that made the emergency call is high and raises the rescue priority level based on determining that the vehicle that made the emergency call is at a standstill and that the location information of the vehicle that made the emergency call has changed.

A method for rendering media content is provided. One example method includes: receiving call signaling of the call service from a call session control device; obtaining call context information of the user equipment; and enabling, based on the call context information, the user equipment to render media content.

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. The system includes a scorecard interface operable to select a target and an indication of the metric control to apply for the target, and to apply the metric control to generate and display a historical performance visualization and a performance feed of the metric for the target.

Implementations relate to determination and visual display of spoken menus for calls. In some implementations, a computer-implemented method includes receiving audio data output in a call between a call device and a device associated with a target entity. The audio data includes speech indicating one or more selection options for a user of the call device to navigate through a call menu provided by the target entity in the call. Text is determined by programmatically analyzing the audio data, the text representing the speech. The selection options are determined based on programmatically analyzing at least one of the text or the audio data. At least a portion of the text is displayed by the call device during the call, as one or more visual options that correspond to the selection options. The visual options are each selectable via user input to cause corresponding navigation through the call menu.

A system and method for secure storage and management of transitory data, comprising at least a profile manager, a callback manager, a context analysis engine, and a vault manager, which allows a user to create a data container to store data preferences, which encrypts the data stored within a data container, which creates a password for accessing the data container, which temporarily stores the data container, which manages data container interactions between the system user and a second user, such as a business enterprise, and which establishes default preferences and creates a default container based upon context content data.

An observation platform comprises a computer system associated with an organization, a first communication device associated with a first user, a second communication device communicatively coupled with the computer system, and a plurality of additional communication devices associated with different users of a plurality of additional users. The computer system communicates with the first and additional communication devices via the second communication device. The computer system receives, via the second communication device, a signal from the first communication device. A characteristic of the signal corresponds to audible source which is a voice of the first user. The computer system derives context information from a speech to text analysis of the characteristic. The context information comprises a query about the organization. The computer system compiles a response to the query and responds based on the compiled response, via the second communication device, to the first communication device about the query.