Methods for detecting fraud include receiving a plurality of call interactions; extracting a voice print of a caller from each of the call interactions; determining which call interactions are associated with a single caller by comparing and matching pairs of voice prints of the call interactions; organizing the call interactions associated with a single caller into a group; and determining that a matching phrase was spoken by the single caller in a first call interaction and second call interaction in the group.

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 system includes a client device including a processor, a telephony radio that supports telephony communications, and a data radio that supports data communications. The client device conducts, via the telephony radio, a call with a telephony service. Further the client device identifies a context of the call, identifies a subset of stored private data associated with the context of the call; and in parallel with the call, provides the subset of the stored private data, via a data radio, to a data service.

A system for automatic authentication of service requests includes authentication of a remote access device. This authentication may be accomplished automatically prior to text or audio communication between a customer and a service agent. In some embodiments, authentication is accomplished automatically by authentication of the remote access device or accomplished by asking the customer questions. A single authentication of the remote access device may be used to authenticate a service request transferred between service agents. The authentication of the remote device may include, for example, use of a personal identification number, a fingerprint, a photograph, and/or a hardware identifier. Some embodiments include an intelligent pipeline configured for managing queues of customer service requests and/or customer service agent control over a customer's access device. Some embodiments include logic configured to manage and enhance communication channels between devices.

Systems and methods are described to enable a device of a user to automatically join an ongoing conference, where the device is not currently joined to the conference. A first audio signature is generated based on voices of users already in the conference, and a second audio signature is generated based on an audio signal captured by a microphone of the device associated with the first user when the device associated with the first user was not joined to the conference. The first audio signature and the second audio signature are compared, and in response to determining that first audio signature matches the second audio signature, the device associated with the first user is joined to the conference.

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 system and method for authenticating an identity may include generating a first generic representation representing a stored audio content, generating a second generic representation representing input audio content, and, providing the first and second generic representations to a voice biometrics unit adapted to authenticate an identity based on the first and second generic representations.

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.

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.

An anti-communications fraud apparatus 1 includes: an analysis unit 13 that analyzes a voiceprint of a communication voice of a calling party; a determination unit 14 that acquires, from a database 17 in which the voiceprint and a degree of fraud risk are stored in association with each other, the degree of fraud risk corresponding to the voiceprint of the calling party, and determines whether the degree of fraud risk exceeds a predetermined threshold; and a notification unit 15 that notifies that the calling party is dangerous when the degree of fraud risk exceeds the threshold.