Receiving a telephone call to an auto-attendant, artificial intelligence, or person takes place. While this phone call is being conducted, a speech to text transcription is created and sent in real-time to another person at another network node. This person can read the transcript and interact with the phone call by sending his or her own commands, text, or speech to be made part of the phone call.

A virtual assistant server receives a web request such as a HTTP request with one or more call parameters corresponding to a call redirected from an interactive voice response server. The virtual assistant server inputs the received one or more call parameters to a predictive model, which identifies, based on the one or more call parameters, an intelligent communication mode to route the redirected call to. Subsequently, the virtual assistant server routes the redirected call to the intelligent communication mode.

A computerized method of terminating audio telephone calls that provides the other party with more information as to why the telephone call was terminated. This method, which is particularly useful for computerized smartphones equipped with voice and data channel communications methods, automatically provides the user with a variety of different informative text messages that can be selected by the user and sent to the other party at the time that a voice call is terminated.

The present disclosure relates to a field of intelligent communications, and discloses a speech communication system and method with human-machine coordination, which resolve a problem of bad client experience because great differences occur after a switchover in a call through a prior human-machine coordination and time of a client is wasted. Key points of the technical solutions of the present disclosure include a communications module; an answering and calling-out module, allocating a human agent; a speech intention understanding module for understanding an intention in a call process; a voice cloning module, synthesizing, from a reply text, voice of a corresponding attendant; a human-machine interaction module, to communicate with a client by a speech robot; an intervention prompting module, monitoring call content to obtain an intervention willing probability, and prompting the human agent according to a predefined rule; and a manual intervention module, through which the client is replied by a person, and the manual intervention module displays a call intention and prompts the call during the call. In this way, during the call, a seamless switchover may be performed between the human agent and the speech robot. After the manual intervention, the attendant can quickly understand the call intention, to ensure good call experience of the client.

A method for controlling a real-time communication between at least two participants can include identifying, from the at least two participants a first participant as an active speaker in the conversation by using audio signals received from the first participant via a microphone, and activating the digital assistant unit for the first participant. A voice recognition procedure for identifying and transcribing identified voice commands can be used so the transcribed voice commands are analyzed and executed.

A method for controlling a real-time communication between at least two participants can include identifying, from the at least two participants a first participant as an active speaker in the conversation by using audio signals received from the first participant via a microphone, and activating the digital assistant unit for the first participant. A voice recognition procedure for identifying and transcribing identified voice commands can be used so the transcribed voice commands are analyzed and executed.

A system described herein may provide a technique for a multi-modal interaction experience with a User Equipment (“UE”) via multiple concurrent presentation modes. Such multiple modes may include a voice call with an interactive voice response (“IVR”) system, as well as the simultaneous presentation of information and/or selectable options at a UE associated engaged in the voice call with the IVR system. The information may be presented via a graphical user interface at the UE that is engaged in the call with the IVR system. In this manner, the UE may provide a multi-modal experience to a user, in which the user can simultaneously interact with the IVR system via the call, and can also receive or provide further interactions related to call via the GUI.

A system and method for omnichannel voice and text-based routing, transfer, and customer-to-enterprise communications with a secure smart mobile user device. The system is a cloud-based network containing an interaction control server, a routing engine, an optimization engine, a media translation server, a mobile application, a business entity portal, mobile and compute devices for business enterprise and customer, and an enterprise database. Taken together or in part, said system optimizes customer interactions by delivering context aware text message, chat or email to customers; and when requested by customer, optimally routes with context, based upon a multitude of variables, to best available resource to handle the customer interaction. The system may be accessed through web browsers, purpose-built computer, mobile phone applications or a secure smart mobile user device.

A device, system and method for modifying actions associated with an emergency call is provided. A mobile device operates a virtual assistant application, which connects to an emergency call that includes a dispatcher and a caller communicating on the emergency call. The mobile device monitors, using the virtual assistant application, the emergency call to determine context information of the emergency call. The mobile device receives, at the virtual assistant application, sensor data from sensors associated with the mobile device. The mobile device correlates, using the virtual assistant application, the context information with the sensor data. The mobile device causes, using the virtual assistant application, a modification of an action associated with the emergency call based on a correlation between the context information with the sensor data.

Techniques and architectures for implementing a team of virtual assistants are described herein. The team may include multiple virtual assistants that are configured with different characteristics, such as different functionality, base language models, levels of training, visual appearances, personalities, and so on. The characteristics of the virtual assistants may be configured by trainers, end-users, and/or a virtual assistant service. The virtual assistants may be presented to end-users in conversation user interfaces to perform different tasks for the users in a conversational manner. The different virtual assistants may adapt to different contexts. The virtual assistants may additionally, or alternatively, interact with each other to carry out tasks for the users, which may be illustrated in conversation user interfaces.