Abstract: A computer-implemented technique is described herein for expediting a user's interaction with a digital assistant. In one implementation, the technique involves receiving a system prompt generated by a digital assistant in response to an input command provided by a user via an input device. The technique then generates a predicted response based on linguistic content of the system prompt, together with contextual features pertaining to a circumstance in which the system prompt was issued. The predicted response corresponds to a prediction of how the user will respond to the system prompt. The technique then selects one or more dialogue actions from a plurality of dialogue actions, based on a confidence value associated with the predicted response. The technique expedites the user's interaction with the digital assistant by reducing the number of system prompts that the user is asked to respond to.

Abstract: A computer-implemented technique is described herein for expediting a user's interaction with a digital assistant. In one implementation, the technique involves receiving a system prompt generated by a digital assistant in response to an input command provided by a user via an input device. The technique then generates a predicted response based on linguistic content of the system prompt, together with contextual features pertaining to a circumstance in which the system prompt was issued. The predicted response corresponds to a prediction of how the user will respond to the system prompt. The technique then selects one or more dialogue actions from a plurality of dialogue actions, based on a confidence value associated with the predicted response. The technique expedites the user's interaction with the digital assistant by reducing the number of system prompts that the user is asked to respond to.

Abstract: Developer and runtime environments supporting multi-modal input for computing systems are disclosed. The developer environment includes a gesture library of human body gestures (e.g., hand gestures) that a previously-trained, system-level gesture recognition machine is configured to recognize. The developer environment further includes a user interface for linking a gesture of the gesture library with a semantic descriptor that is assigned to a function of the application program. The application program is executable to implement the function responsive to receiving an indication of the gesture recognized by the gesture recognition machine within image data captured by a camera. The semantic descriptor may be additionally linked to a different input modality than the gesture, such as a natural language input.

Abstract: Developer and runtime environments supporting multi-modal input for computing systems are disclosed. The developer environment includes a gesture library of human body gestures (e.g., hand gestures) that a previously-trained, system-level gesture recognition machine is configured to recognize. The developer environment further includes a user interface for linking a gesture of the gesture library with a semantic descriptor that is assigned to a function of the application program. The application program is executable to implement the function responsive to receiving an indication of the gesture recognized by the gesture recognition machine within image data captured by a camera. The semantic descriptor may be additionally linked to a different input modality than the gesture, such as a natural language input.

Abstract: Developer and runtime environments supporting multi-modal input for computing systems are disclosed. The developer environment includes a gesture library of human body gestures (e.g., hand gestures) that a previously-trained, system-level gesture recognition machine is configured to recognize. The developer environment further includes a user interface for linking a gesture of the gesture library with a semantic descriptor that is assigned to a function of the application program. The application program is executable to implement the function responsive to receiving an indication of the gesture recognized by the gesture recognition machine within image data captured by a camera. The semantic descriptor may be additionally linked to a different input modality than the gesture, such as a natural language input.

Abstract: A computer-implemented technique is described herein for expediting a user's interaction with a digital assistant. In one implementation, the technique involves receiving a system prompt generated by a digital assistant in response to an input command provided by a user via an input device. The technique then generates a predicted response based on linguistic content of the system prompt, together with contextual features pertaining to a circumstance in which the system prompt was issued. The predicted response corresponds to a prediction of how the user will respond to the system prompt. The technique then selects one or more dialogue actions from a plurality of dialogue actions, based on a confidence value associated with the predicted response. The technique expedites the user's interaction with the digital assistant by reducing the number of system prompts that the user is asked to respond to.

Abstract: A computer-implemented technique is described herein for expediting a user's interaction with a digital assistant. In one implementation, the technique involves receiving a system prompt generated by a digital assistant in response to an input command provided by a user via an input device. The technique then generates a predicted response based on linguistic content of the system prompt, together with contextual features pertaining to a circumstance in which the system prompt was issued. The predicted response corresponds to a prediction of how the user will respond to the system prompt. The technique then selects one or more dialogue actions from a plurality of dialogue actions, based on a confidence value associated with the predicted response. The technique expedites the user's interaction with the digital assistant by reducing the number of system prompts that the user is asked to respond to.

Abstract: Developer and runtime environments supporting multi-modal input for computing systems are disclosed. The developer environment includes a gesture library of human body gestures (e.g., hand gestures) that a previously-trained, system-level gesture recognition machine is configured to recognize. The developer environment further includes a user interface for linking a gesture of the gesture library with a semantic descriptor that is assigned to a function of the application program. The application program is executable to implement the function responsive to receiving an indication of the gesture recognized by the gesture recognition machine within image data captured by a camera. The semantic descriptor may be additionally linked to a different input modality than the gesture, such as a natural language input.

Abstract: Developer and runtime environments supporting multi-modal input for computing systems are disclosed. The developer environment includes a gesture library of human body gestures (e.g., hand gestures) that a previously-trained, system-level gesture recognition machine is configured to recognize. The developer environment further includes a user interface for linking a gesture of the gesture library with a semantic descriptor that is assigned to a function of the application program. The application program is executable to implement the function responsive to receiving an indication of the gesture recognized by the gesture recognition machine within image data captured by a camera. The semantic descriptor may be additionally linked to a different input modality than the gesture, such as a natural language input.

Abstract: A computer-implemented technique is described herein for expediting a user's interaction with a digital assistant. In one implementation, the technique involves receiving a system prompt generated by a digital assistant in response to an input command provided by a user via an input device. The technique then generates a predicted response based on linguistic content of the system prompt, together with contextual features pertaining to a circumstance in which the system prompt was issued. The predicted response corresponds to a prediction of how the user will respond to the system prompt. The technique then selects one or more dialogue actions from a plurality of dialogue actions, based on a confidence value associated with the predicted response. The technique expedites the user's interaction with the digital assistant by reducing the number of system prompts that the user is asked to respond to.

Abstract: Developer and runtime environments supporting multi-modal input for computing systems are disclosed. The developer environment includes a gesture library of human body gestures (e.g., hand gestures) that a previously-trained, system-level gesture recognition machine is configured to recognize. The developer environment further includes a user interface for linking a gesture of the gesture library with a semantic descriptor that is assigned to a function of the application program. The application program is executable to implement the function responsive to receiving an indication of the gesture recognized by the gesture recognition machine within image data captured by a camera. The semantic descriptor may be additionally linked to a different input modality than the gesture, such as a natural language input.