Audio Recording Indexing via Handwriting Collaboration Engine
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Solution Overview
Problem
Users face inefficiencies in locating specific portions of recorded audio data, as they must listen to the entire recording to find desired sections, and existing methods fail to accurately determine important sections based on user engagement during recording.
Innovation Solution
An electronic device with a microphone and touch screen capable of detecting handwriting inputs, using a handwriting collaboration engine to determine high-priority sections in audio recordings by counting the number of users or devices performing handwriting, and conditionally displaying these sections in distinct visual styles for easy identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users listen to the entire recorded audio data to find desired sections, then they can locate specific content, but the time required increases significantly
Solution Approach 1:
The system performs preliminary analysis during the recording process by detecting handwriting inputs and marking important sections in real-time. This preliminary action creates a structured index of significant portions before playback, allowing users to directly navigate to desired sections without listening to the entire recording, thus resolving the contradiction between accurate location and time consumption
Solution Approach 2:
The patent introduces an intermediary mechanism (handwriting detection system) that bridges the gap between raw audio data and user information needs. By detecting handwriting inputs as a mediator signal, the system automatically identifies and marks important sections, enabling efficient navigation without manual searching and eliminating the need to listen to entire recordings
2Reliability
If the system marks all sections as potentially important, then no important sections are missed, but the ability to quickly identify high-priority content is reduced
Solution Approach 1:
The system applies local quality by differentiating between various levels of importance among sections. Instead of uniform marking, it uses visual distinction (such as bold formatting or special icons) specifically for sections with detected handwriting inputs, while leaving other sections unmarked or differently marked. This allows users to quickly identify high-priority content through visual cues, resolving the contradiction between completeness and ease of identification
Solution Approach 2:
The patent employs visual differentiation techniques (such as color changes, bold text, or special markers) to distinguish important sections from non-important ones. By changing the visual appearance of sections where handwriting was detected, the system maintains reliable identification of all important content while enabling users to quickly spot high-priority sections through visual contrast, thus resolving the contradiction between reliability and ease of operation
Data Source
AI summary
An electronic device includes a microphone recording audio data comprising first and second sections, a screen capable of detecting input of strokes on a surface thereof, a receiver configured to receive stroke data representing strokes input on other electronic devices during a period of the recording, and a hardware processor. The hardware process is configured to determine a first number of users who performed or devices that processed handwriting inputs in the first section, determine a second number of users who performed or devices that processed handwriting inputs in the second section, conditionally display on the screen a first object representing the first section in a first display style, and conditionally display on the screen a second object representing the second section in a second display style, the first and second numbers being different and the first and second display styles being visually distinguishable from each other.