Retroactive Audio Recording via Trigger-Based Buffering
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Solution Overview
Problem
There is a need for a simplified and enhanced method to capture, store, and share day-to-day conversations and audible events, particularly for retroactive recording and sharing, which existing technologies have not adequately addressed.
Innovation Solution
A system comprising an electronic device and an application program that enables user-selectable audio triggers for continuous recording, real-time monitoring, and automatic transfer of audio signals to storage, allowing for editing and sharing of noteworthy statements through a combination of audio receivers, digital converters, and data storage, with features like user-input triggers, editing functions, and distribution to social media networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous recording is implemented to capture all conversations, then no noteworthy events are missed, but storage space is wasted and managing large volumes of audio becomes difficult
Solution Approach 1:
The system extracts only the noteworthy portions of conversations by using trigger words to identify and save specific segments, rather than storing all audio content. This allows the system to capture important events while minimizing storage space consumption by excluding irrelevant audio data.
Solution Approach 2:
The system pre-loads a buffer of audio data into memory before a trigger word is detected, so that when the trigger occurs, the relevant conversation segment is already prepared and ready for immediate saving. This preliminary buffering action ensures no noteworthy content is missed while avoiding the need to store entire continuous recordings.
2Quantity of substance
If manual recording is used to save noteworthy conversations, then storage space is efficient, but important events may be missed and the process is time-consuming
Solution Approach 1:
The system automatically detects trigger words and saves relevant audio segments without requiring manual user intervention. The automated trigger-based mechanism eliminates the need for users to manually start and stop recordings, making the process effortless while ensuring important events are captured reliably.
Solution Approach 2:
The system provides real-time feedback by detecting trigger words in the audio stream and automatically initiating the save process. This feedback mechanism ensures that noteworthy conversations are captured promptly without requiring user attention or manual operation, significantly reducing user effort.
3Adaptability or versatility
If retroactive recording is implemented to capture past conversations, then noteworthy past events can be saved, but the system complexity increases
Solution Approach 1:
The system continuously pre-loads audio data into a buffer memory in advance, preparing the data structure and metadata needed for potential retroactive retrieval. This preliminary organization of audio segments by time stamps and trigger contexts enables flexible retroactive recording without requiring complex real-time processing when triggers are detected.
Solution Approach 2:
The audio recording is divided into discrete segments with associated metadata including time stamps and trigger contexts. This segmentation allows the system to efficiently retrieve and manage specific past conversations without processing or storing entire continuous audio streams, reducing system complexity while enabling retroactive recording flexibility.
4Speed
If real-time trigger detection is implemented, then noteworthy events are captured immediately, but processing time and computational resources increase
Solution Approach 1:
The system pre-loads a buffer of audio data into memory and pre-processes it for trigger detection, so that when a trigger word occurs, the detection can happen immediately without requiring extensive real-time analysis. This preliminary preparation reduces computational resource consumption during actual trigger events while maintaining fast detection responsiveness.
Solution Approach 2:
The system maintains a buffer larger than strictly necessary, pre-loading more audio data than the minimum required for trigger detection. This excessive buffering allows the system to process triggers faster by having data already in memory, reducing the need for intensive real-time computational resources while maintaining high detection speed.
Data Source
AI summary
An electronic device such as a smart phone, in combination with an application program residing at least partially therein and run at least partially thereby effectively enables selective retroactive recording to capture already-passed audible events when an audible trigger is recognized. When used in conjunction with an internet-based social media network or an interested contact list, audible events that meet certain pre-determined criteria may be automatically shared.