Context-Aware Voice Actions With Dynamic Buttons on Media Devices
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Solution Overview
Problem
Conventional voice-based digital assistants rely on backend components due to computational limitations of electronic devices, failing to leverage the context of voice inputs for personalized and effective actions.
Innovation Solution
A method and system that determines context from natural language inputs on a media device, calculates priority scores for actions, and generates dynamic action buttons for user selection, enabling efficient task execution and power optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If voice-based digital assistants rely on backend components for processing, then computational limitations of electronic devices are avoided, but device complexity increases and response time is delayed
Solution Approach 1:
The patent extracts and implements context determination and action prioritization logic directly within the media device's digital assistant, removing the dependency on backend components for these specific functions. This allows the device to process voice inputs locally for context analysis and action selection, reducing overall system complexity while maintaining reliable task performance.
Solution Approach 2:
The patent segments the voice processing system into distinct functional modules: voice input reception, context determination, action identification, priority scoring, and dynamic button generation. This segmentation allows each component to operate independently and optimally, improving reliability while keeping the overall system manageable in complexity.
2Adaptability or versatility
If conventional digital assistants use basic voice recognition, then device complexity is reduced, but the ability to provide personalized and effective actions is limited
Solution Approach 1:
The patent implements dynamic action buttons that adapt their content and behavior based on the determined context and priority scores. The system dynamically adjusts the interface and action options presented to users according to the voice input context, enabling personalized responses without requiring overly complex processing for every possible scenario.
Solution Approach 2:
The patent changes parameters such as action priority scores and button configurations based on the analyzed context of voice inputs. By adjusting these parameters dynamically, the system provides personalized and effective actions while maintaining manageable processing complexity through rule-based parameter modification rather than complex machine learning models.
3Reliability
If digital assistants perform more comprehensive task analysis, then task performance reliability is improved, but power consumption increases
Solution Approach 1:
The patent performs preliminary context determination and action prioritization before presenting options to the user. By analyzing the voice input and determining context and priority scores in advance, the system prepares appropriate action buttons efficiently, improving task execution reliability while minimizing power consumption through targeted processing rather than continuous heavy analysis.
Data Source
AI summary
Systems and methods for providing contextual based actions based on a natural language input are disclosed. The method comprises: receiving, on a media device, a natural language input; determining, based on the natural language input, a first context of the natural language input; and determining, based on the first context, a first action. a dynamic action button is generated and configured to be selected by a user to carry out an action, and in response to the user selecting the dynamic action button, the systems and methods describe carrying out the first action.