Provided is an emergency dispatch command information management method capable of providing relevant emergency dispatch command information. The method includes: a step of receiving report input data from a reporter terminal; a step of generating reception input data of a recipient on the basis of the report input data; a step of generating first emergency dispatch command information on the basis of the reception input data; a step of detecting at least one second emergency dispatch command information relevant to the generated first emergency dispatch command information; and a step of transmitting the first and second emergency dispatch command information to a command receiver terminal.

A computer-implemented method for real-time modification of notification tones to distinguish an intended recipient of a notification tone is disclosed. The computer-implemented method includes monitoring an audio stream of an online conference for one or more audio notification tones. The computer-implemented method further includes detecting that a notification tone generated outside of the online conference matches the notification tone of an application or user device associated with two or more participants of the online conference. The computer-implemented method further includes responsive to detecting that the notification tone matches the notification tone of an application or user device associated with two or more participants of the online conference, generating an ameliorative action associated with the notification tone.

A call captioning system for captioning a hearing user's (HU's) voice signal during an ongoing call with an assisted user (AU) includes: an AU communication device with a display screen and a caption service activation feature, and a first processor programmed to, during an ongoing call, receive the HU's voice signal. Prior to activating the caption service via the activation feature, the processor uses an automated speech recognition (ASR) engine to generate HU voice signal captions, detect errors in the HU voice signal captions, use the errors to train the ASR software to the HU's voice signal to increase accuracy of the HU captions generated by the ASR engine; and store the trained ASR engine for subsequent use. Upon activating the caption service during the ongoing call, the processor uses the trained ASR engine to generate HU voice signal captions and present them to the AU via the display screen.

Systems and methods are provided for automatically selecting a mute function based on audio content. One example method includes receiving, at a first computing device, a first audio input and, from a second computing device, a second audio input. Content of the first audio input and the second audio input is determined with natural language processing. Whether the content of the first audio input corresponds to the content of the second audio input is determined. A mute function is operated at the first computing device, based on the determination of whether the content of the first audio input corresponds to the content of the second audio input.

Secure system and method of detecting and preventing inmate to inmate message relays. A system and method which monitors inmate communications for similar phrases that occur as part of two or more separate inmate messages. These similar phrases may be overlapping in real time as in a conference call or can occur at separate times in separate messages. The communications that appear similar are assigned a score and the score is compared to a threshold. If the score is above a certain threshold, the communication is flagged and remedial actions are taken. If the flagged communication contains illegal matter then the communication can be disconnected or restricted in the future.

Systems and methods for assessing the skills of a customer support agent using one or more Artificial Intelligence/Machine Learning (AI/ML) models are disclosed. In at least one embodiment, one or more benchmarks against which the performance of the customer support agent is to be measured are established. The one or more benchmarks may be derived through direct and/or indirect analysis of historical customer service data by an AI/ML benchmark model. In at least one embodiment, data relating to performance of the customer support agent during a customer call is monitored. In at least one embodiment, the AI/ML benchmark model is used to determine one or more benchmark scores identifying whether the customer support agent is meeting the one or more benchmarks.

Certain exemplary aspects of the present disclosure are directed to a data-communications system including a networked contact center for which, in an example embodiment, a communication is received by a networked contact center. In determining whether to allow the communication to reach contact center resources, a contact rate value is examined. The contact rate value may represent an allowable quantity of contact within a time interval. For some example embodiments, a determination of whether the network contact center is to accept or reject the communication is made based on the contact rate value.

In some embodiments, a system and method for generating phrase based categories of interactions may include obtaining a base category, the base category including one or more phrases. A base trend for the base category may be generated based on a frequency of appearance of at least one of the one or more phrases in a set of recorded interactions; a candidate phrase may be obtained and a candidate trend may be generated for the candidate phrase based on a frequency of appearance of the candidate phrase in the set of recorded interactions; a correlation level may be determined by relating the candidate trend to the base trend; and, if the correlation level is greater than a threshold level then the candidate phrase may be included the in the base category.

This document discusses, among other things, limiting contact to a networked contact center that is a host to multiple tenants. In an example embodiment, a communication is received by a networked contact center. In determining whether to allow the communication to reach contact center resources, a contact rate value may be examined. The contact rate value may represent an allowable quantity of contact within a time interval. For some example embodiments, a determination of whether the network contact center is to accept or reject the communication is made based on the contact rate value.

A method facilitating a cross-channel interaction between a customer and a contact center. The method includes: receiving and conducting a first interaction with the customer; determining a first identifier related to the first interaction; storing, in a database, the first identifier and associating the first identifier with the first interaction; receiving a second interaction from the customer; determining a second identifier related to the second interaction; using the second identifier to check the database to determine if the second interaction is associated with the first interaction; determining, based on the check of the database, that the second interaction is contextually related with the first interaction; and modifying, in response to determining that the second interaction is contextually related to the first interaction, at least one way in which the second interaction is handled by the contact center.