Introduced here is a platform for actively managing communication channels. In particular, the communication channels are managed to increase the probability of success of a call center agent to meaningfully engage with a client. In addition, the platform provides identification information and other information to facilitate a conversation between the parties, while also reducing the pre-call preparation by an agent. The platform parses search results to identify contact information for prospect by utilizing keyword identification algorithm. During the call, the platform applies voice detection and speaker detection algorithms to ensure that the agent is speaking with a live voice, rather than a pre-recorded message. By applying these algorithms, the platform aims to increase call center efficiency and conversation rates, while reducing pre-call preparation and skepticism of a prospect.

The present invention provides an effective means of screening calls by sharing contact data between individual users of communication devices. The contact information is augmented to include shareability data and relations data. The additional data can be used to configure the shared data in a way that private contacts, for example, can be restricted from sharing, while public contacts are shared.

Embodiments of the present invention provide methods, computer program products, and systems. Embodiments of the present invention can create an authentication mechanism for communication services utilizing a distributed recording system. Embodiments of the present invention can then, in response to receiving a request to connect with a device, utilize the created authentication mechanism to connect with or prevent connection with the device.

Aspects of the subject disclosure may include, for example, a method of receiving, by a processing system including a processor, a call for a subscriber; determining, by the processing system, that the call is from an interactive voice response (IVR) system; determining whether the IVR system is providing a query that requires a response; and responsive to a first determination that the IVR system requires the response, providing the response. Other embodiments are disclosed.

Implementations described herein relate to methods, systems, and computer-readable media to label incoming phone calls. A method to label an incoming phone call includes detecting the incoming phone call associated with a caller identifier (ID), determining a location associated with the call, and analyzing a call header of the call to determine one or more call characteristics. The method further includes determining, based on the location and the call characteristics, if the location is spoofed and determining, based on the caller ID and the call characteristics, if an access network associated with the call is spoofed. The method further includes applying a trained machine learning model to determine whether the call is a robocall. The method further includes assigning a label to the call that indicates whether the call is a spoofed call or is the robocall and sending the label to a callee device associated with the call.

Introduced here is a platform for actively managing communication channels. In particular, the communication channels are managed to increase the probability of success of a call center agent to meaningfully engage with a client. In addition, the platform provides identification information and other information to facilitate a conversation between the parties, while also reducing the pre-call preparation by an agent. The platform parses search results to identify contact information for prospect by utilizing keyword identification algorithm. During the call, the platform applies voice detection and speaker detection algorithms to ensure that the agent is speaking with a live voice, rather than a pre-recorded message. By applying these algorithms, the platform aims to increase call center efficiency and conversation rates, while reducing pre-call preparation and skepticism of a prospect.

Methods and systems for detecting an answering machine/voicemail system using a machine learning model are provided herein. In some embodiments, a method for detecting an answering machine/voicemail system using a machine learning model comprises receiving an audio stream from a telecommunication session; parsing the audio stream into a plurality of audio files; converting each of the plurality of audio files into an image; inputting each of the converted images into the machine learning model; receiving a prediction from the machine learning model; sending an indication that an answering machine/voicemail system is detected when the received prediction is a beep.

A contact center system for performing call progress analysis including tone and speech classification according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the contact center system to determine a cumulative average of an entropy of an audio signal received by the contact center system, determine a cumulative average power spectral amplitude and a cumulative average spectral entropy of the audio signal, calculate a difference measure of the audio signal as a difference between the cumulative average of the entropy and the cumulative average spectral entropy, distinguish tones from speech of the audio signal based on the difference measure, and process one or more tones of the audio signal in response to identification of the one or more tones in the audio signal.

A method and system for automatically blocking robocalls. A set of incoming call data is captured from the incoming call. The set of incoming call data, including captured audio data, is checked with plural different tests to determine if the robocall includes a voice call component. The plural different tests provide additional levels of detection for robocalls. The method and system automatically identify and process robocalls and help prevent call spoofing and neighbor spoofing by robocalls.

Disclosed herein are systems and methods for determining whether an automated telephone call has been answered by a particular user, a different person, or a voicemail service. In response to determining that the call has been answered by the user, a different person, or a voicemail service, the systems and methods can output different respective messages, initiate messaging to the user via alternate communication paths, or perform other actions.