An apparatus for providing automated analysis and monitoring of an ABT session is presented herein. The apparatus may include a display configured to present material for the ABT session to a patient, at least one video capture device configured to capture video data for the ABT session related to at least one of first facial features of the patient, second facial features of a therapist, or a response to the material presented on the display, at least one audio capture device configured to capture audio data for the ABT session related to at least one of a first voice of the patient or a second voice of the therapist, and at least one processor configured to analyze, for the ABT session, data regarding the material presented on the display, the captured video data, and the captured audio data to produce an analysis of the ABT session.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating and operating voice conversing virtual agents with pre-modeled and inherited human behavior across use cases and domains. One of the methods includes: using a first non-domain specific neural network based model to predict a non-domain specific conversational situation, the first neural network based model trained with labelled parts of conversations from more than one domain; forwarding the non-domain specific conversational situation to a second domain specific neural network based model; using the second domain specific neural network based model to predict a conversational situation and to provide a system intent, the second domain specific neural network based model trained with labelled parts of conversation from a specified domain; and generating a response based at least in part on the predicted conversational situation and system intent.

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.

A method of generating an emotion descriptor icon includes receiving input content comprising video information, and performing analysis on the input content to produce information representing the video information with respect to a plurality of characteristics. The method also includes determining, based on a comparison of the information representing the video information at a temporal position in the video information and a set of information items respectively representing an emotion state, a relative likelihood of association between the input content and at least some of a plurality of emotion states, selecting an emotion state based on the outcome of the determination, and outputting an emotion descriptor icon selected from an emotion descriptor icon set comprising a plurality of emotion descriptor icons. The outputted emotion descriptor icon is associated with the selected emotion state.

A method of generating an emotion descriptor icon includes receiving input content comprising video information, and performing analysis on the input content to produce information representing the video information with respect to a plurality of characteristics. The method also includes determining, based on a comparison of the information representing the video information at a temporal position in the video information and a set of information items respectively representing an emotion state, a relative likelihood of association between the input content and at least some of a plurality of emotion states, selecting an emotion state based on the outcome of the determination, and outputting an emotion descriptor icon selected from an emotion descriptor icon set comprising a plurality of emotion descriptor icons. The outputted emotion descriptor icon is associated with the selected emotion state.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, relating to synthetic call status updates. In some implementations, a method includes determining, by a task manager module, that a triggering event has occurred to provide a current status of a user call request. The method may then determine, by the task manager module, the current status of the user call request. A representation of the current status of the user call request is generated. Then, the generated representation of the current status of the user call request is provided to the user.

A device provides audible output pertaining to audio video (AV) content such as a video game based on a section of the AV content that is being presented.

A device provides audible output pertaining to audio video (AV) content such as a video game based on a section of the AV content that is being presented.

Systems, methods, and other embodiments associated with computer distress-call detection and authentication are described. In one embodiment, a method includes detecting a human voice in audio content of a radio signal. Speech is recognized in the human voice to transform the human voice into text and vocal metrics. Feature scores are generated that represent features of the recognized speech based at least in part on the vocal metrics. The human voice is then classified as either a hoax distress call or an authentic distress call based on the feature scores. An alert is then presented indicating that the human voice is one of the hoax distress call or the authentic distress call.

Systems, methods, and other embodiments associated with computer distress-call detection and authentication are described. In one embodiment, a method includes detecting a human voice in audio content of a radio signal. Speech is recognized in the human voice to transform the human voice into text and vocal metrics. Feature scores are generated that represent features of the recognized speech based at least in part on the vocal metrics. The human voice is then classified as either a hoax distress call or an authentic distress call based on the feature scores. An alert is then presented indicating that the human voice is one of the hoax distress call or the authentic distress call.