Audio-Video Drift Mitigation via Temporal Metadata
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Solution Overview
Problem
Conventional audiovisual editing techniques introduce temporal drift between audio and video tracks due to non-sample boundary edits, leading to perceptible lag or lead, which degrades the user experience in streaming media.
Innovation Solution
A method to mitigate temporal drift by determining whether to include or exclude video frames in the presentation timeline based on their alignment with sample boundaries, calculating and managing the resulting temporal drift, and transmitting metadata to endpoint devices to adjust audio delay parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If edits are made at non-sample boundaries to achieve precise creative intent, then editing flexibility is improved, but temporal drift between audio and video tracks increases
Solution Approach 1:
The system performs preliminary calculations of temporal drift during the editing process, before final rendering. By computing the accumulated drift from multiple edits in advance, the system can predict and compensate for synchronization issues before they manifest in the final output, thus maintaining both editing flexibility and temporal precision.
Solution Approach 2:
Metadata serves as an intermediary carrier that transports temporal drift information from the editing system to the playback system. This metadata acts as a bridge, allowing the playback system to apply appropriate compensation without requiring changes to the core audio or video streams, thus preserving editing flexibility while correcting synchronization drift.
2Adaptability or versatility
If multiple edits are accumulated in a media file, then content customization is improved, but perceptible lag between audio and video tracks increases
Solution Approach 1:
The system implements feedback by calculating the accumulated temporal drift from multiple edits and encoding this information in metadata. The playback system reads this feedback information and adjusts audio timing accordingly, creating a closed-loop system that maintains synchronization reliability even with multiple custom edits.
Solution Approach 2:
The system changes the audio delay parameter dynamically based on the calculated accumulated temporal drift. By adjusting this parameter in response to the number and type of edits, the system maintains audio-video synchronization while allowing extensive content customization through multiple edits.
3Measurement precision
If edits enter or exit tracks at non-sample boundaries, then creative precision is improved, but temporal drift calculation complexity increases
Solution Approach 1:
The system segments the temporal drift calculation into manageable components by processing each edit individually and accumulating the results. This segmentation allows precise handling of non-sample boundary edits while keeping the overall calculation complexity manageable through systematic breakdown of the problem into discrete, processable units.
Data Source
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AI summary
One embodiment of the present invention sets forth a technique for mitigating drift in audiovisual assets. The technique includes determining that an edit associated with a presentation timeline is within boundaries of a video frame. The technique further includes calculating a temporal drift associated with the edit, where the temporal drift comprises a duration of time between the edit and a boundary of the video frame. The technique further includes determining whether to include the video frame in the presentation timeline based on the temporal drift and an accumulated temporal drift associated with the presentation timeline.