Multimodal Assistant Responses Using Live Visual Context
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Solution Overview
Problem
Existing intelligent automated assistants lack the ability to efficiently integrate visual context into user interactions, requiring multiple inputs and increasing cognitive burden on users.
Innovation Solution
Implementing a digital assistant system that integrates visual context through live camera feeds, allowing users to provide inputs and receive responses based on real-time visual information, reducing the need for manual input and enhancing interaction efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing intelligent automated assistants process user requests using only text or speech input, then the system complexity remains low, but the user interaction efficiency deteriorates due to requiring multiple inputs and increasing cognitive burden
Solution Approach 1:
The patent combines multiple input modalities (text, speech, and visual context from camera feeds) into a unified processing framework. The digital assistant integrates visual context information from the camera with traditional text/speech inputs, allowing users to interact more naturally by pointing the camera at objects or scenes relevant to their requests, thereby reducing the number of inputs required and lowering cognitive burden while maintaining manageable system complexity through modular integration.
2Loss of information
If the digital assistant integrates visual context from camera feeds, then the relevance of responses improves, but the power consumption increases
Solution Approach 1:
The system implements periodic or event-driven camera feed processing rather than continuous processing. The digital assistant activates visual context analysis selectively when triggered by specific user actions (e.g., when a user points the camera at an object or indicates visual input is desired), allowing the device to consume power only when visual context enhancement is beneficial, thereby maintaining response relevance while managing power consumption through intermittent operation.
3Speed
If the system processes camera data in real-time to provide visual context, then the interaction responsiveness improves, but the processing time and computational load increase
Solution Approach 1:
The system performs preliminary processing of camera data by pre-extracting key visual features and maintaining a condensed visual context representation that can be quickly queried. Instead of processing full-resolution camera feeds in real-time, the digital assistant pre-processes visual information to extract essential contextual elements (such as object identification, scene classification, or key visual markers) that can be rapidly matched with user requests, thereby improving interaction responsiveness while reducing actual processing time during user interactions.
Data Source
AI summary
Systems and processes for operating an intelligent automated assistant are provided. Example methods include displaying a representation of a current field-of-view of a camera and, while displaying the representation, generating responses to user inputs based on context information determined from the current field-of-view of the camera.