Audio Video Sync via Pause Gap Analysis
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Solution Overview
Problem
Existing techniques for synchronizing audio and video streams during network bandwidth issues require sophisticated object detection analysis, which is resource-intensive for real-time processing.
Innovation Solution
A method using pause gap analysis, where audio and video streams are split to identify pause gaps, a binary classifier predicts sound presence or absence, and metadata is used to align desynchronized pause gaps, enabling efficient synchronization without heavy runtime processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sophisticated object detection analysis (e.g., lip sync) is used for synchronization, then synchronization accuracy is improved, but computational resource consumption and processing complexity increase significantly
Solution Approach 1:
The patent extracts and utilizes pause gaps (silent segments) from audio and video streams as synchronization markers, eliminating the need for complex object detection and lip sync analysis. By focusing only on the temporal presence/absence of sound rather than analyzing visual content, the system achieves synchronization with minimal computational resources.
Solution Approach 2:
The invention uses simple pause gap detection as a low-cost proxy for complex synchronization analysis. Instead of investing heavy computational resources in sophisticated object detection, the system employs a lightweight approach that detects only the temporal patterns of silence, providing sufficient synchronization accuracy without the computational burden.
2Measurement precision
If sophisticated object detection analysis is used for synchronization, then synchronization accuracy is improved, but runtime processing time increases
Solution Approach 1:
The patent extracts and utilizes pause gaps (silent segments) from audio and video streams as synchronization markers, eliminating the need for complex object detection and lip sync analysis. By focusing only on the temporal presence/absence of sound rather than analyzing visual content, the system achieves synchronization with minimal computational resources.
Solution Approach 2:
The system performs preliminary detection of pause gaps in both audio and video streams before synchronization is needed. By pre-identifying these temporal markers and storing their metadata, the system can quickly align streams without performing expensive real-time analysis during the actual synchronization process.
3Productivity
If pause gap analysis with binary classifier is used, then processing efficiency is improved, but synchronization precision may be compromised
Solution Approach 1:
The patent employs a binary classifier that receives feedback from pause gap detection and adjusts its predictions accordingly. The classifier is trained on the temporal patterns of pause gaps and continuously refines its ability to predict sound presence/absence, ensuring high synchronization precision while maintaining processing efficiency.
Solution Approach 2:
The system changes the parameters of analysis from complex visual object detection to temporal audio patterns. By transforming the synchronization problem into a temporal pattern recognition task focused on pause gaps, the system achieves both high efficiency and precision through parameter transformation rather than algorithmic complexity.
Data Source
AI summary
A computer-implemented method, a computer program product, and a computer system for synchronizing audio and video using pause gap analysis. A computer splits a video into an audio stream and a video stream. A computer identifies time points at which there is no sound in the audio stream and derives pause gaps in the audio stream. A computer applies a binary classifier to predict sound presence or absence in frames of the video stream and derives pause gaps in the video stream. A computer identifies desynchronization between the pause gaps in the video stream and the pause gaps in the audio stream. A computer aligns the pause gaps in the video stream with the pause gaps in the audio stream, based on metadata of the pause gaps in the video stream.