Systems, methods, and computer-readable media for call classification and for training a model for call classification, an example method comprising: receiving DTMF information from a plurality of calls; determining, for each of the calls, a feature vector including statistics based on DTMF information such as DTMF residual signal comprising channel noise and additive noise; training a model for classification; comparing a new call feature vector to the model; predicting a device type and geographic location based on the comparison of the new call feature vector to the model; classifying the call as spoofed or genuine; and authenticating a call or altering an IVR call flow.

When an incoming call is received from a customer, various aspects may include receiving an indication of availability from several call agents within the computer-telephony integration system and presenting the indications of availability and identification information for each of the call agents on a display. A user control for searching the call agents may also be presented on the display for use by a first call agent to view an indication of availability for a particular call agent. The customer call may then be transferred from the first call agent to the particular call agent in response to the indication of availability identifying the particular call agent as available.

An enhanced routing system determines a service provider best suited to fulfill a user's request to interact and establishes a communication session between the user's client device and a device of the service provider. The enhanced routing system may use user characteristics and behavior to select the service provider. For example, the enhanced routing system receives a request to connect to a customer service system from a user who has recently started a new job and has been accessing a banking application on his mobile phone. The enhanced routing system may determine that a payroll service provider is best suited to fulfill the user's request. For example, the enhanced routing system uses a machine learning model that has been trained on previously fulfilled requests. In this way, the enhanced routing system improves upon systems that continuously prompt the user for information by selecting a service provider without overburdening the user.

A system is described herein that facilitates the monitoring of inmate communications. The system provides a remotely-accessible means for a reviewer to monitor a call between an inmate and another person. The system includes a monitoring server and a monitoring station. The monitoring server is configured to receive a call and call information from a communication center and process the call for monitoring, schedule a review of the call; and store the call, the call information, and scheduling data. The monitoring station is configured to receive the call and the call information from the monitoring server based on the scheduling data, and to display the identifying information and facilitate the review of the call.

A system for authenticating the identity of a caller (i) receives a phone call from a caller, where the phone call is initiated through an application on a remote computer device associated with the caller, and where the phone call includes one or more phone authentication credentials; (ii) determines a preliminary identity of the caller based upon the one or more phone authentication credentials; (iii) receives online authentication credentials from the application on the remote computer device; (iv) determines a confirmed identity of the caller based, at least in part, upon the one or more online credentials and the preliminary identity of the caller; and (v) displays the confirmed identity of the caller to a user answering the phone call. As a result, the user and/or the system do not need to perform additional authentication before providing service to the caller.

An enhanced routing system determines a service provider best suited to fulfill a user's request to interact and establishes a communication session between the user's client device and a device of the service provider. The enhanced routing system may use user characteristics and behavior to select the service provider. For example, the enhanced routing system receives a request to connect to a customer service system from a user who has recently started a new job and has been accessing a banking application on his mobile phone. The enhanced routing system may determine that a payroll service provider is best suited to fulfill the user's request. For example, the enhanced routing system uses a machine learning model that has been trained on previously fulfilled requests. In this way, the enhanced routing system improves upon systems that continuously prompt the user for information by selecting a service provider without overburdening the user.

Systems, methods, and computer-readable media for call classification and for training a model for call classification, an example method comprising: receiving DTMF information from a plurality of calls; determining, for each of the calls, a feature vector including statistics based on DTMF information such as DTMF residual signal comprising channel noise and additive noise; training a model for classification; comparing a new call feature vector to the model; predicting a device type and geographic location based on the comparison of the new call feature vector to the model; classifying the call as spoofed or genuine; and authenticating a call or altering an IVR call flow.

The present invention relates to a method for routing communications in a telecommunications network comprising a first telephony user device and a server system. The method includes at the first telephony user device: receiving instructions to initiate communications with a contact associated with an address; initiating communications via a channel within the telecommunications network to a local address for the server system; and transmitting information associated with the contact address to the server system via the telecommunications network. A communications action is performed in relation to the contact at the server system. Other methods, devices, systems and networks for routing communications are disclosed.

Broadband communications devices and methods operate with at least two separate communication paths between the devices and the network, such as the Internet. The broadband devices and methods receive data concurrently over the communication paths or separately. The bandwidth is increased when the separate communication paths are combined. The broadband devices employ packetized data with Voice over Internet Protocol (VoIP) technologies combined with RF communications technologies.

An alert generator in a communication system for processing a call includes at least one machine learning model generating call classifiers from outputs of an audio signal processor and a natural language processor configure to operate on the call. Heuristic logic is configured to transform the call classifiers into a plurality of weighted sub-metrics for the call, and aggregate normalized Gaussian logic is configured to transform the weighted sub-metrics into a metric control. A threshold analyzer is configured to generate an alert signal to the communication system based on the metric control meeting a condition.