Audio-Video Synchronization Using Compressive Audio Signatures
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Maintaining synchronization between audio and video streams, particularly when audio is created subsequent to video, is challenging due to desynchronization issues that can be detected by users even at the level of tens or hundreds of milliseconds, leading to a disconcerting viewing experience.
Innovation Solution
The approach involves decomposing the synchronization process into two steps: synchronizing video with original audio and then synchronizing non-original audio with the original audio using audio signatures generated through compressive sensing matrices, allowing for rapid matching and correction of desynchronization errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If non-original audio streams are created subsequent to video capture, then audio translation and localization are enabled, but synchronization errors between audio and video streams increase
Solution Approach 1:
The patent segments the audio stream into multiple alternative audio streams (original audio, dubbed audio, commentary audio) and processes each separately. The synchronization system compares timestamps and content of each audio stream against the video stream independently, enabling precise synchronization control for each alternative audio track without affecting others.
Solution Approach 2:
The patent introduces an intermediary synchronization mechanism that uses timestamp metadata and content comparison as intermediate steps. The system inserts synchronization markers and uses intermediate reference points (such as scene transitions or distinctive audio-visual events) to align non-original audio streams with the video stream, bridging the temporal gap created by separate production processes.
2Manufacturing precision
If manual synchronization adjustments are made for each audio stream, then synchronization accuracy improves, but processing time and resource consumption increase
Solution Approach 1:
The patent performs preliminary synchronization actions during the audio stream creation and encoding process. Timestamp metadata is embedded into the audio streams in advance, and synchronization information is pre-calculated and stored. This preliminary preparation eliminates the need for time-consuming manual adjustment during deployment, as the system can automatically apply pre-computed synchronization offsets.
Solution Approach 2:
The synchronization system is designed to be self-service through automated timestamp comparison and offset calculation algorithms. The system automatically detects synchronization drift, calculates required adjustments, and applies corrections without human intervention. This self-service capability maintains high synchronization accuracy while eliminating manual processing bottlenecks.
3Manufacturing precision
If resource-intensive neural network techniques are used for synchronization, then synchronization accuracy improves, but computational cost and processing time increase
Solution Approach 1:
The patent employs lightweight, computationally efficient synchronization algorithms that use simple timestamp comparison and linear offset calculation instead of resource-intensive neural networks. These inexpensive computational methods process synchronization data rapidly and are discarded after each synchronization event, providing adequate accuracy for most applications without the high computational cost of deep learning models.
Solution Approach 2:
The system dynamically changes synchronization parameters based on the specific characteristics of each audio-video pair. Instead of using a fixed complex model, the algorithm adjusts synchronization offsets, sampling rates, and comparison thresholds according to the actual drift patterns observed in each stream, achieving adaptive accuracy with minimal computational overhead.
Data Source
AI summary
Systems and methods are provided for detecting and correcting synchronization errors in multimedia content comprising a video stream and a non-original audio stream. Techniques for directly detecting synchronization of video and audio streams may be inadequate to detect synchronize errors for non-original audio streams, particularly where such non-original audio streams contain audio not reflective of events within the video stream, such as speaking dialog in a different language than the speakers of the video stream. To overcome this problem, the present disclosure enables synchronization of a non-original audio stream to another audio stream, such as an original audio stream, that is synchronized to the video stream. By comparison of signatures, the non-original and other audio stream are aligned to determine an offset that can be used to synchronize the non-original audio stream to the video stream.