The graphical programming call router features a rich library of powerful and easy-to-use components that administrators can use to seamlessly drop in contact center actions such as data dips, complex interactive voice responses (“IVRs”) and call recordings, among many others. This makes it easy to visualize the exact structure and outcome of any call flow. The graphical programming call router also offers granular queue management functionality so you can get specific around call prioritization, wait time and time-based actions on virtual queues.

Implementations are directed to providing a voice bot development platform that enables a third-party developer to train a voice bot based on training instance(s). The training instance(s) can each include training input and training output. The training input can include a portion of a corresponding conversation and a prior context of the corresponding conversation. The training output can include a corresponding ground truth response to the portion of the corresponding conversation. Subsequent to training, the voice bot can be deployed for conducting conversations on behalf of a third-party. In some implementations, the voice bot is further trained based on a corresponding feature emphasis input that attentions the voice bot to a particular feature of the portion of the corresponding conversation. In some additional or alternative implementations, the voice bot is further trained to interact with third-party system(s) via remote procedure calls (RPCs).

A virtual assistant system for communicating with customers uses human intelligence to correct any errors in the system AI, while collecting data for machine learning and future improvements for more automation. The system may use a modular design, with separate components for carrying out different system functions and sub-functions, and with frameworks for selecting the component best able to respond to a given customer conversation. The system may have agent assistance functionality that uses natural language processing to identity concepts in a user conversation and to illustrate that concepts within a graphical user interface of a human agent so that the human agent can more accurately and more rapidly assist the user in accomplishing the user's conversational objectives.

A method for incorporating an augmented voice communication into a communication routing configuration of a contact center system according to an embodiment includes selecting a vocal avatar, wherein the vocal avatar includes phonetic characteristics having first values, receiving a text communication and input user parameters from an input user, generating the augmented voice communication based on the text communication and the input user parameters, wherein the augmented voice communication includes phonetic characteristics having second values, wherein the first values of the phonetic characteristics of the vocal avatar are different from the second values of the phonetic characteristics of the augmented voice communication, and incorporating the augmented voice communication into the communication routing configuration of the contact center system.

A method for incorporating an augmented voice communication into a communication routing configuration of a contact center system according to an embodiment includes selecting a vocal avatar, wherein the vocal avatar includes phonetic characteristics having first values, receiving a text communication and input user parameters from an input user, generating the augmented voice communication based on the text communication and the input user parameters, wherein the augmented voice communication includes phonetic characteristics having second values, wherein the first values of the phonetic characteristics of the vocal avatar are different from the second values of the phonetic characteristics of the augmented voice communication, and incorporating the augmented voice communication into the communication routing configuration of the contact center system.

An example method includes receiving, by a computational assistant executing at one or more processors, a representation of an utterance spoken at a computing device; identifying, based on the utterance, a task to be performed by the computational assistant; responsive to determining, by the computational assistant, that complete performance of the task will take more than a threshold amount of time, outputting, for playback by one or more speakers operably connected to the computing device, synthesized voice data that informs a user of the computing device that complete performance of the task will not be immediate; and performing, by the computational assistant, the task.

An example operation may include one or more of receiving a data file comprising a list of interactive voice response (IVR) prompts, identifying a set of IVR prompts within the received data file that are included within a common sequence, assembling text content from each IVR prompt in the set of IVR prompts within the common sequence into a string of text content, and modifying the data file to include the assembled string of text content within a field of the modified data file.

A user experience workflow may be configured based on input received for various object types selectively arranged within the user experience workflow and then bound to a destination identifier, such as a telephone number or web address. A user interface of software for configuring a user experience workflow is presented at a user device and input from that user device is used to selectively arrange objects within a user experience workflow and/or to configure objects thereof. After configurations are applied to the objects, the user experience workflow is bound to the destination identifier. An end user device which accesses the destination identifier (e.g., by calling the telephone number, visiting the web address, or using an application connecting to the web address) may then traverse the user experience workflow, including in some cases having configured content presented thereto.

Certain aspects of the disclosure are directed to customization of a contact center, using a data communications server. According to a specific example, the data communications server includes circuitry configured and arranged to provide data communications services to a plurality of remotely-situated client entities. The data communications server further provides a user interface for each respective remotely-situated client entity, the user interface including a display of communications-based campaigns, interactive voice response (IVR) tools, and data analytics. Moreover, the data communications server provides a display on the user interface which may include selectable components to create for the associated remotely-situated client entity, a customized way for handling incoming data communications by the data communications server. Accordingly, the data communications server may handle communications for the associated remotely-situated client entity according to the provided customization.

In some implementations, a computing device may receive a selection of one or more contact center features, the contact center features associated with one or more micro services configured to execute the one or more contact center features. The computing device may select a model from a plurality of stored models based at least in part on the selection of the one or more contact center features, the selected model comprising programmable code configured to execute the one or more micro services. The computing device may provision the selected model to execute the one or more micro services. The computing device may generate executable code from the provisioned model using an automation server for deployment to one or more servers.