Customers can become bored with an interaction with an agent. By providing speech and/or images, of a celebrity disguising the speech, and/or image, of the agent, customers can appear to interact with a particular celebrity. As a result, customers are more likely to stay engaged and have a positive experience. The celebrity, or a particular persona of a celebrity, may be selected from customer preferences and/or a purpose of the call. For example, a movie star's role may have a persona, such as a “heavy,” suitable for collection calls (audio or audio-video), whereas a scientific or technical innovator may be selected for technical support calls.

Customers can become bored with an interaction with an agent. By providing speech and/or images, of a celebrity disguising the speech, and/or image, of the agent, customers can appear to interact with a particular celebrity. As a result, customers are more likely to stay engaged and have a positive experience. The celebrity, or a particular persona of a celebrity, may be selected from customer preferences and/or a purpose of the call. For example, a movie star's role may have a persona, such as a “heavy,” suitable for collection calls (audio or audio-video), whereas a scientific or technical innovator may be selected for technical support calls.

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, and/or computing entities for processing a call drop likelihood prediction for an interactive call data object. In accordance with one embodiment, a method is provided that includes: identifying a group of interactive call feature data objects associated with the interactive call data object that comprises an interactive call audio data object and an interactive call metadata object; processing the call feature data objects using a real-time call monitoring machine learning framework to generate the prediction by: processing the call audio data object using an audio data processing machine learning model to generate an audio-based embedding data object, processing the call audio data object using an audio transcript processing machine learning model to generate a transcript-based embedding data object, and generating the prediction based at least in part on the audio-based and transcript-based embedding data objects and the metadata object.

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, and/or computing entities for processing a call drop likelihood prediction for an interactive call data object. In accordance with one embodiment, a method is provided that includes: identifying a group of interactive call feature data objects associated with the interactive call data object that comprises an interactive call audio data object and an interactive call metadata object; processing the call feature data objects using a real-time call monitoring machine learning framework to generate the prediction by: processing the call audio data object using an audio data processing machine learning model to generate an audio-based embedding data object, processing the call audio data object using an audio transcript processing machine learning model to generate a transcript-based embedding data object, and generating the prediction based at least in part on the audio-based and transcript-based embedding data objects and the metadata object.

A method and system are disclosed herein for accepting multimodal inputs and deriving synchronized and processed information. A reusable multimodal application is provided on the mobile device. A user transmits a multimodal command to the multimodal platform via the mobile network. The one or more modes of communication that are inputted are transmitted to the multimodal platform(s) via the mobile network(s) and thereafter synchronized and processed at the multimodal platform. The synchronized and processed information is transmitted to the multimodal application. If required, the user verifies and appropriately modifies the synchronized and processed information. The verified and modified information are transferred from the multimodal application to the visual application. The final result(s) are derived by inputting the verified and modified results into the visual application.

A method and system are disclosed herein for accepting multimodal inputs and deriving synchronized and processed information. A reusable multimodal application is provided on the mobile device. A user transmits a multimodal command to the multimodal platform via the mobile network. The one or more modes of communication that are inputted are transmitted to the multimodal platform(s) via the mobile network(s) and thereafter synchronized and processed at the multimodal platform. The synchronized and processed information is transmitted to the multimodal application. If required, the user verifies and appropriately modifies the synchronized and processed information. The verified and modified information are transferred from the multimodal application to the visual application. The final result(s) are derived by inputting the verified and modified results into the visual application.

A technique for message history display includes combining message histories for multiple different messaging services. A system constructed according to the technique may include, for example, a message history database; a history aggregation engine that aggregates message logs for storage in the message history database; and a history provisioning engine that provides an aggregated message log associated with the user from the message history database to a requesting device. A method according to the technique may include, for example, identifying a device in association with a user profile; providing an online platform that receives messages from and sends messages to the device; and creating an aggregated log from messages sent to and from the device.

A technique for message history display includes combining message histories for multiple different messaging services. A system constructed according to the technique may include, for example, a message history database; a history aggregation engine that aggregates message logs for storage in the message history database; and a history provisioning engine that provides an aggregated message log associated with the user from the message history database to a requesting device. A method according to the technique may include, for example, identifying a device in association with a user profile; providing an online platform that receives messages from and sends messages to the device; and creating an aggregated log from messages sent to and from the device.

A contact information system provides an independent network authority for providing contact information in connection with incoming calls or messages. The contact information system utilizes a database of communication identifiers to provide contact information for end user devices that receive incoming communications which specify communication identifiers that are stored in the database.

A secure payment agent assist (“SPAA”) feature provides assistance to a contact center agent during a transaction involving sensitive information, where the sensitive information provided by the remote party is maintained in secure manner, so that the agent is not exposed to it. The agent is assisted by being provided with a pop-up window that allows the agent to invoke a “recollect” and “cancel” function during the transaction. The pop-up window also provides information to the agent making the agent aware of the progress of the transaction as the remote party interacts with an interactive voice response (“IVR”) unit. In other embodiments, a configuration parameter allows the prompts for the payment information to be provided by the agent or the IVR.