A system and method for intent-based active callback management using enhanced callback objects, utilizing a cloud callback system comprising at least a profile manager, callback manager, interaction manager, media server, and environment analyzer, allowing users to call businesses, agents in contact centers, or other users who are connected to a cloud callback system, and, failing to connect to the individual they called, allow for an automatic callback object to be created, whereby the two users may be automatically called and bridged together at a time when both users are available.

Artificial intelligence (Al) based technologies for improving patient appointment scheduling and inventory management are disclosed herein. An example method includes receiving, at a server including a natural language processing (NLP) model, an appointment request from a user. The example method further includes initiating, based on the appointment request, a patient appointment data stream including verbal responses from the user regarding an appointment of the user. The example method further includes applying, while simultaneously receiving the patient appointment data stream, the NLP model to the verbal responses from the user to output (i) textual transcriptions and (ii) intent interpretations. The example method further includes querying a scheduling database to determine a matching appointment that satisfies a distance threshold, a date threshold, a service threshold, and an inventory threshold. The example method further includes causing a user device of the user to convey the matching appointment to the user.

Systems and methods of design, delivery, and analysis of customer feedback surveys include receiving interaction content. Interaction content is analyzed to identify at least one issue arising in the interaction content. A survey of a plurality of questions is automatedly created based upon the identified at least one issue. A delivery channel for the survey is determined. The survey is delivered through the determined delivery channel. A survey response with survey results data is received.

The present disclosure provides a call processing method, apparatus, electronic device and storage medium and relates to the field of cloud computing. The method may comprise: obtaining a calling subscriber's status information in real time while an intelligent dialogue robot is used to make a call with the calling subscriber; when it is determined that a call form of the intelligent dialogue robot needs to be adjusted, correspondingly adjusting the call form of the intelligent dialogue robot according to current status information of the calling subscriber. The solution of the present disclosure may be employed to improve the call performance of the intelligent dialogue robot.

A system and method is provided for providing searchable customer call indexes. Consistent with disclosed embodiments, a system may receive call information associated with telephone conversations between callers and a vendor, the call information including an audio recording or transcript for each telephone conversation. The system may also identify one or more keywords from the audio recordings or transcripts and index the call information into one or more indexes based on the identified keywords. Finally, the system may determine search results responsive to a search query based on the indexing. In some embodiments, changes to customer service may be identified based on the search results.

In a method for handling out-of-sequence caller dialog, an intelligent voice interface is configured to lead callers through pathways of an algorithmic dialog that includes available voice prompts for requesting different types of caller information. The method may include, during a voice communication with a caller via a caller device, receiving from the caller device caller input data indicative of a voice input of the caller, without having first provided to the caller device any voice prompt that requests a first type of caller information, and determining, by processing the caller input data, that the voice input includes caller information of the first type. The method also includes after determining that the voice input includes the caller information of the first type, bypassing one or more voice prompts, of the available voice prompts, that request the first type of caller information.

Automated systems and methods are provided for processing natural language, comprising obtaining first and second digitally-encoded speech representations, respectively corresponding to an agent script for and a voice recording of a telecommunication interaction; generating a similarity structure based on the speech representations, the similarity structure representing a degree of semantic similarity between the speech representations; matching markers in the first speech representation to markers in the second speech representation based on the similarity structure; and dividing the telecommunication interaction into a plurality of sections based on the matching.

A call captioning system for captioning a hearing user's (HU's) voice signal during an ongoing call with an assisted user (AU) includes: an AU communication device with a display screen and a caption service activation feature, and a first processor programmed to, during an ongoing call, receive the HU's voice signal. Prior to activating the caption service via the activation feature, the processor uses an automated speech recognition (ASR) engine to generate HU voice signal captions, detect errors in the HU voice signal captions, use the errors to train the ASR software to the HU's voice signal to increase accuracy of the HU captions generated by the ASR engine; and store the trained ASR engine for subsequent use. Upon activating the caption service during the ongoing call, the processor uses the trained ASR engine to generate HU voice signal captions and present them to the AU via the display screen.

This disclosure describes, in part, techniques for establishing network-based data communications (e.g., voice calls, video calls, etc.) between a user device of a user and a remote device of another user, and transitioning the data communications to a different user device of the user based on various types of information. In some examples, the user devices may be located in one or more environments of the user, and the data communications may be transitioned between the user devices based, at least in part, on a location of the user in the environment(s) relative to the multiple devices. For instance, if a user device is performing data communications with the remote device, but it is determined that the user has moved into a closer proximity to another user device, the performance of the data communications may be transitioned to the other user device to which the user is in closer proximity.

A computer-implemented method for providing an objective evaluation to a customer service representative regarding his performance during an interaction with a customer may include receiving a digitized data stream corresponding to a spoken conversation between a customer and a representative; converting the data stream to a text stream; generating a representative transcript that includes the words from the text stream that are spoken by the representative; comparing the representative transcript with a plurality of positive words and a plurality of negative words; and generating a score that varies according to the occurrence of each word spoken by the representative that matches one of the positive words, and/or the occurrence of each word spoken by the representative that matches one of the negative words. Tone of voice, as well as response time, during the interaction may also be monitored and analyzed to adjust the score, or generate a separate score.