Audio Drift Normalization for Simultaneous Multi-Device Recording
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Solution Overview
Problem
Current systems for recording and uploading audio and video files are inefficient, requiring complete session recording before upload, leading to increased time and costs, and struggle with audio drift issues that necessitate additional hardware and manual correction processes.
Innovation Solution
A method that allows for simultaneous recording and uploading of multiple files with audio drift normalization, using algorithms and software to eliminate manual processes, normalize audio drift, and enable synchronized recordings on low-end devices, reducing the need for local storage and backend engineering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complete session recording is performed before upload, then data accessibility is ensured, but upload time and system resource requirements increase
Solution Approach 1:
The patent divides the recording session into discrete segments or chunks that can be uploaded independently as they are completed. Instead of waiting for the entire session to finish recording before uploading, the system processes and uploads segments in real-time or near-real-time, reducing total upload time while maintaining data accessibility through progressive availability of recording portions.
2Manufacturing precision
If additional hardware and systems are used to correct audio drift, then recording quality improves, but device complexity and costs increase
Solution Approach 1:
The patent replaces complex hardware-based audio synchronization systems with software-based audio drift normalization algorithms. Instead of using additional hardware devices to physically synchronize multiple recording sources, the system uses computational methods to detect and correct timing drift in audio recordings post-capture, achieving high recording quality without increased hardware complexity.
3Measurement precision
If manual correction processes are used for audio drift, then synchronization accuracy improves, but productivity decreases
Solution Approach 1:
The patent implements automated audio drift normalization that performs synchronization corrections without human intervention. The system self-adjusts timing drift between multiple audio recordings using algorithmic detection and correction methods, eliminating the need for manual post-production work while maintaining high synchronization accuracy, thereby significantly improving production efficiency.
4Reliability
If multiple recording devices are used to capture conversations, then data redundancy and accessibility improve, but audio drift and synchronization issues worsen
Solution Approach 1:
The patent introduces an intermediary processing layer that receives audio recordings from multiple devices and applies normalization algorithms to synchronize them. This intermediary system acts as a mediator between the diverse recording sources and the final output, detecting timing drift patterns and applying corrective transformations to align all recordings, thereby maintaining data accessibility from multiple sources while resolving synchronization issues.
Data Source
AI summary
The invention relates to audio drift normalization, and more particularly to audio drift normalization systems and methods that can normalize audio drift of a plurality of recordings from a source.