A method and apparatus of applying user profile information to a customized application are disclosed. One example method of operation may include receiving an inquiry message or call from a user device, identifying and authorizing the user from inquiry message information received from the inquiry message, retrieving a user profile comprising at least one user preference, applying the at least one user preference to a user call processing application, and transmitting menu options to the user device based on the applied at least user preference.

Controlled-environment communication systems are increasingly using voice over internet protocol (VoIP) to serve their users. VoIP allows voice to be sent in packetized form, where audio is encoded using one of several codecs. Because of bandwidth constraints, particularly during peak call times, codecs may be used which sacrifice audio quality for bandwidth efficiency. As a result, several features of communication systems, including critical security features. The present disclosure provides details for systems and methods by which a controlled-environment communication system may shift between codecs to perform security-related features or to alleviate bandwidth considerations. This involves the special formatting of control-signaling messages, including session initiation protocol (SIP) and session description protocol (SDP) messaging.

Systems and methods for analyzing digital recordings of the human voice in order to find characteristics unique to an individual. A biometrics engine may use an analytics service in a contact center to supply audio streams based on configured rules and providers for biometric detection. The analytics service may provide call audio data and attributes to connected engines based on a provider-set of selection rules. The connected providers send call audio data and attributes through the analytics service. The engines are notified when a new call is available for processing and can then retrieve chunks of audio data and call attributes by polling an analytics service interface. A mathematical model of the human vocal tract in the call audio data is created and/or matched against existing models. The result is analogous to a fingerprint, i.e., a pattern unique to an individual to within some level of probability.

A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform steps of a method for detecting harassment. The system may receive communication data from a first customer service representative terminal or a customer communication device and may determine, based at least in part on the communication data and stored communication data, that the communication data comprises harassing content. The system may, responsive to determining that the communication data comprises harassing content, transmit to a second customer service representative terminal, a notification indicating that the communication data comprises harassing content.

One embodiment provides a method comprising answering one or more incoming phone calls received at one or more pre-specified phone numbers utilizing a bot. The bot is configured to engage in a conversation with a caller initiating an incoming phone call utilizing a voice recording that impersonates a human being. The method further comprises recording each conversation the bot engages in, and classifying each recorded conversation as one of poison data or truthful training data based on content of the recorded conversation and one or more learned detection models for detecting poisoned data.

A computer-implemented method for determining potentially undesirable voices, according to some embodiments, includes: receiving a plurality of audio recordings, the plurality of audio recordings comprising voices associated with undesirable activity, and determining a plurality of audio components of each of the plurality of audio recordings. The method may further comprise generating a multi-dimensional vector of audio components, from the plurality of audio components, for each of the plurality of audio recordings to generate a plurality of multi-dimensional vectors of audio components, and comparing audio components between the plurality of multi-dimensional vectors of audio components to determine a plurality of clusters of multi-dimensional vectors, each cluster of the plurality of clusters comprising two or more of the plurality of multi-dimensional vectors of audio components, wherein each cluster of the plurality of clusters corresponds to a blacklisted voice. The method may further comprise receiving an audio recording or audio stream, and determining whether the audio recording or audio stream is associated with a voice associated with undesirable activity based on a comparison to the plurality of clusters.

Provided are a call deflection and response system and method, wherein a voice call from a caller device is received, a skill group is determined to resolve an issue associated with the call, and a text response to the issue is sent to the caller device, providing a context-based personalized response. A caller leaves a detailed voicemail explaining an issue needing resolution, which is electronically transcribed and then run through a classifier to determine concepts and intents associated with the call. Based on the concepts and intents, responsibility for the call and associated files are transferred to a particular skill group on a chat platform for resolution. A chat entity from the appropriate skill group determines and provides an issue response via text message to the caller device, e.g., to the caller's mobile phone.

While a teleconference is occurring, data of a teleconference is analyzed to determine first participant data associated with a first speaker and second participant data associated with a second speaker. At a different application, addition of a first speaker indicator and a second speaker indicator to a text entry of a user is caused, the first speaker indicator added concurrently with identification that the first speaker is speaking and the second speaker indicator added concurrently with identification that the second speaker is speaking. At the different application, addition of key information to a text entry of a user is caused, the key information comprising participant data associated with the first speaker and second participant data associated with the second speaker.

Provided are voiceprint recognition method, device, terminal apparatus and storage medium. The method comprises: allocating each agent to the corresponding group according to their calling authorities, collecting and processing voiceprint features of each agent in the group to obtain integrated voiceprint features of the group, building a dynamic voiceprint recognition model based on the grouping, calling authority and integrated voiceprint features, acquiring voice data of agent when a call operation from the agent is detected, performing voiceprint feature extraction, meanwhile determining the calling authority of the agent based on a dynamic voiceprint recognition model; if the calling authority of the to-be-identified agent does not meet the required customer level, executing a preset early warning processing measure, and further monitoring; judging the group to which the agent belongs through voiceprint recognition, and realizing real-time monitoring according to the corresponding relation between the group and the authority.

A system and method for fraud detection and management are provided. The system includes a first communication device that receives a phone call from a second communication device, wherein a call flow of the phone call comprises one or more distinct phases. The system also includes a fraud detection and management system (FDMS) platform that determines whether the phone call exceeds a predetermined risk threshold at each distinct phase of the call flow.