A notification control apparatus (2000) acquires video data or audio data for a plurality of persons (10) (a human group (40)) who have a conversation within a predetermined distance with each other in a surveillance area. The notification control apparatus (2000) determines whether or not the human group (40) is in a state suitable for receiving a notification using the acquired data. When the human group (40) is in the state suitable for receiving the notification, the notification control apparatus (2000) issues a predetermined notification.

A notification control apparatus (2000) acquires video data or audio data for a plurality of persons (10) (a human group (40)) who have a conversation within a predetermined distance with each other in a surveillance area. The notification control apparatus (2000) determines whether or not the human group (40) is in a state suitable for receiving a notification using the acquired data. When the human group (40) is in the state suitable for receiving the notification, the notification control apparatus (2000) issues a predetermined notification.

A method and apparatus to generate and update virtual personification using artificial intelligence comprising a system configured to perform the following. Receive data associated with a person such as text files, audio files, image files, and video files. Render a virtual personification of the person and output the virtual personification to a user, such as on a display screen. Then, receiving and interpreting a user input to generate a user request, and then updating the virtual personification. The update may include generating an audio output using the text files and the audio files of the person and/or generating a video output using the image files and the video files of the person. The audio output and the video output is presented to the user by the virtual personification and it has not previously occurred by the person or thing represented by the virtual personification.

A method and apparatus to generate and update virtual personification using artificial intelligence comprising a system configured to perform the following. Receive data associated with a person such as text files, audio files, image files, and video files. Render a virtual personification of the person and output the virtual personification to a user, such as on a display screen. Then, receiving and interpreting a user input to generate a user request, and then updating the virtual personification. The update may include generating an audio output using the text files and the audio files of the person and/or generating a video output using the image files and the video files of the person. The audio output and the video output is presented to the user by the virtual personification and it has not previously occurred by the person or thing represented by the virtual personification.

Methods and systems provide for extracting engaging questions from a communication session. In one embodiment, the system connects to a communication session with a number of participants; receives a transcript of a conversation between the participants produced during the communication session; extracts, from the transcript, utterances including one or more sentences spoken by the participants; identifies a subset of the utterances spoken by a subset of the participants associated with a prespecified organization; extracts engaging questions within the subset of utterances, the engaging questions each including a question asked by the participant associated with the organization that is immediately answered in the following utterance by a participant not associated with the organization; and presents, for display at one or more client devices, data corresponding to the extracted engaging questions.

Methods and systems provide for extracting engaging questions from a communication session. In one embodiment, the system connects to a communication session with a number of participants; receives a transcript of a conversation between the participants produced during the communication session; extracts, from the transcript, utterances including one or more sentences spoken by the participants; identifies a subset of the utterances spoken by a subset of the participants associated with a prespecified organization; extracts engaging questions within the subset of utterances, the engaging questions each including a question asked by the participant associated with the organization that is immediately answered in the following utterance by a participant not associated with the organization; and presents, for display at one or more client devices, data corresponding to the extracted engaging questions.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for status monitoring using machine vision and machine learning. In some implementations, image data representing a monitored area is obtained. Input data based on the image data is provided to one or more machine learning models trained to detect different properties of the monitored area. Output of the one or more machine learning models is received. The output of the one or more machine learning models is evaluated to detect a condition present in the monitored area. Output is provided indicating the detected condition present in the monitored area.

System and method for determining an outcome probability of an event based on videos are disclosed. The method includes receiving the videos of an event, creating a building block model, extracting one of an audio content, a video content from the videos, analysing extracted content, generating an analysis result, analysing an engagement between speaker and participant of event, generating a data lake comprising a keyword library, computing the outcome probability of the event, enabling the building block model to learn from the data lake and the outcome probability computed and representing the at least one outcome probability in a pre-defined format.

System and method for determining an outcome probability of an event based on videos are disclosed. The method includes receiving the videos of an event, creating a building block model, extracting one of an audio content, a video content from the videos, analysing extracted content, generating an analysis result, analysing an engagement between speaker and participant of event, generating a data lake comprising a keyword library, computing the outcome probability of the event, enabling the building block model to learn from the data lake and the outcome probability computed and representing the at least one outcome probability in a pre-defined format.

Systems and methods for generating real-time synthetic crowd responses for events, to augment the experience of event participants, remote viewers, and the like. Various sensors monitor the event in question, and various event properties are derived from their output using an event state model. These event properties, along with various event parameters such as score, time remaining, etc., are then input to a machine learning model that determines a real-time synthetic audience reaction tailored to the immediate state of the event. Reaction parameters are used to generate a corresponding crowd or audience audio signal, which may be broadcast to event participants, viewers, spectators, or anyone who may be interested. This instantaneous, realistic crowd reaction more closely simulates the experience of events with full on-site audiences, enhancing the viewing experience of both event participants and those watching.