Digital Assistant Media Discovery via Natural Language Context
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Solution Overview
Problem
Existing methods for discovering media based on nonspecific, unstructured natural language requests are cumbersome and inefficient, requiring complex user interfaces and excessive time, which is impractical for hands-free or battery-operated devices.
Innovation Solution
A digital assistant system that receives user input in unstructured natural language, identifies context, and searches for media items to satisfy the request, allowing for faster and more efficient media discovery on devices with processors, memory, and microphones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing techniques are used to discover media based on nonspecific natural language requests, then users can access media information, but the process is cumbersome and time-consuming requiring multiple key presses and user research
Solution Approach 1:
The system performs media discovery autonomously by analyzing the natural language request to identify context, selecting appropriate media items, and presenting them to the user without requiring manual search or multiple inputs. The digital assistant independently completes the media discovery task that would otherwise require extensive user intervention.
Solution Approach 2:
The patent replaces mechanical keyboard inputs and manual search operations with natural language speech recognition. Users communicate media requests through spoken words, and the system processes these linguistic inputs to automatically retrieve and present relevant media, eliminating the need for physical key presses and manual navigation.
2Adaptability or versatility
If existing techniques are used for media discovery, then users can find media information, but the process requires complex user interfaces and excessive time which is impractical for hands-free or battery-operated devices
Solution Approach 1:
The digital assistant integrates multiple functions into a single unified system that handles media discovery, context analysis, and user interaction through natural language. This multi-functional approach eliminates the need for separate complex interfaces for different operations, providing a universal solution that works effectively in hands-free scenarios and on battery-operated devices.
3Productivity
If existing techniques are used for media discovery, then users can access media, but the process wastes user time and device energy which is particularly important in battery-operated devices
Solution Approach 1:
The system performs preliminary context analysis and media selection based on the natural language request before presenting options to the user. By pre-processing the request to identify relevant context and pre-select appropriate media items, the system reduces the overall time and energy required for media discovery, as less processing is needed after the user's initial input.
Data Source
AI summary
An exemplary method for identifying media may include receiving user input associated with a request for media, where that user input includes unstructured natural language speech including one or more words; identifying at least one context associated with the user input; causing a search for the media based on the at least one context and the user input; determining, based on the at least one context and the user input, at least one media item that satisfies the request; and in accordance with a determination that the at least one media item satisfies the request, obtaining the at least one media item.