Methods and systems are disclosed herein for improving the quality of audio for use in a biometric. A biometric system may use machine learning to determine whether audio or a portion of the audio should be used as a biometric for a user. A sample of the user's voice may be used to generate a voice signature of the user. Portions of the audio that do not meet a similarity threshold when compared with the voice signature may be removed from the audio. Additionally or alternatively, interfering noises may be detected and removed from the audio to improve the quality of a voice biometric generated from the audio.

A distributed voice applications system includes a voice applications rendering agent and at least one voice applications agent that is configured to provide voice applications to an individual user. A management system may control and direct the voice applications rendering agent to create voice applications that are personalized for individual users based on user characteristics, information about the environment in which the voice applications will be performed, prior user interactions and other information. The voice applications agent and components of customized voice applications may be resident on a local user device which includes a voice browser and speech recognition capabilities. The local device, voice applications rendering agent and management system may be interconnected via a communications network.

A communication system includes a communication control section including a first control section configured to broadcast utterance voice data received from one of mobile communication terminals to other mobile communication terminals and a second control section configured to chronologically accumulate a result of utterance voice recognition from voice recognition processing on the received utterance voice data as a user-to-user communication history and to control text delivery such that the communication history is displayed on the mobile communication terminals in synchronization; and a utterance voice evaluation section configured to perform voice quality evaluation processing on the received utterance voice data and to output a result of voice quality evaluation. The communication control section is configured to control text delivery such that the result of voice recognition based on the utterance voice and the result of voice quality evaluation are displayed on the user terminals.

The present invention makes it possible to efficiently create an appropriate dialogue history. This device for supporting creation of dialogue history (1) is provided with: a dialogue utterance focus point information store (19) which, according to utterance data indicating utterances, stores dialogue scene data indicating dialogue scenes of the utterances, utterance type indicating the types of the utterances, and utterance focus point information of the utterances; and an input/output interface (20) which, with respect to each of the dialogue scenes indicated by the dialogue scene data stored in the dialogue utterance focus point information store (19), causes a display device to display any one or more of utterances, utterance type, and utterance focus point information. Based on an operation input to the input/output interface (20), the dialogue utterance focus point information store (19) adds, modifies, or deletes any one or more of the dialogue scene data, the utterance type, and the utterance focus point information.

Disclosed is a secure telephone call management system for authenticating users of a telephone system in an institutional facility. Authentication of the users is accomplished by using a personal identification number, preferably in conjunction with speaker independent voice recognition and speaker dependent voice identification. When a user first enters the system, the user speaks his or her name which is used as a sample voice print. During each subsequent use of the system, the user is required to speak his or her name. Voice identification software is used to verify that the provided speech matches the sample voice print. The secure system includes accounting software to limit access based on funds in a user's account or other related limitations. Management software implements widespread or local changes to the system and can modify or set any number of user account parameters.

Systems and methods are provided for dynamic generation of staff analytics and forecasts based on skill and service level. Dynamic forecasting allows for forecast generation in real-time and may be based on historical data regarding skills and results, as well as data science to identify patterns and make predictions. The resulting staffing forecast may therefore provide for efficient management of messaging staff costs while preserving the desired service quality. The staffing forecast may include a volume forecast that is tailored to the unique nature of asynchronous messaging, as well as the unique messaging needs of the entity so as to efficiently manage messaging operations and make data-driven staffing decisions that take service level into account. An exemplary embodiment may include dynamic analytics tools that may use specified target and/or resource numbers (e.g., desired service level) for an existing messaging operation and get a detailed per-skill staffing forecast.

Aspects of the subject disclosure may include, for example, detecting, over a network, a call originating from a call originator and intended for a user of a user equipment, responsive to the detecting the call, determining whether to challenge the call originator, based on a determination to challenge the call originator, transmitting a request to the call originator, wherein the request prompts the call originator to specify an identity of the call originator and a purpose for the call, obtaining information from a call originator input responsive to the transmitting the request, deriving enhanced Caller Name or Caller ID data that includes the information, and causing the enhanced Caller Name or Caller ID data to be provided to the user equipment, thereby enabling the user of the user equipment to determine whether to answer the call. Other embodiments are disclosed.

Disclosed embodiments may include a system that may receive an audio file comprising an interaction between a first user and a second user. The system may detect, using a deep neural network (DNN), moment(s) of interruption between the first and second users from the audio file. The system may extract, using the DNN, vocal feature(s) from the moment(s) of interruption. The system may determine, using a machine learning model (MLM) and based on the vocal feature(s), whether a threshold number of moments of the moment(s) of interruption corresponds to a first emotion type. When the threshold number of moments corresponds to the first emotion type, the system may transmit a first message comprising a first binary indication. When the threshold number of moments do not correspond to the first emotion type, the system may transmit a second message comprising a second binary indication.

A system for data recording across a network includes a session border controller connecting incoming data from the network to an endpoint recorder. A load balancer is connected to the network between the session border controller and the endpoint and receives the incoming data from the session border controller, wherein the load balancer comprises computer memory and a processor configured to parse the incoming data into video data and audio data according to identification protocols accessible by the processor from the computer memory. A recording apparatus includes recording memory that receives the incoming data from the load balancer, stores a duplicate version of the incoming data in the recording memory, and connects the incoming data to the endpoint.

A system and method for securely recording voice communications, comprising a network-connected computer server and an authentication system which verifies the validity of voice communications.