Live Stream Targeted Content Splicing with Unknown Break Markers
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Solution Overview
Problem
Existing streaming platforms face difficulties in seamlessly inserting targeted content into live broadcast streams due to unknown insertion points and durations, leading to 'dead air' and abrupt cutoffs, especially when providing highly customized content in real-time.
Innovation Solution
A system that generates a computing model of targeted content recommendations, buffers pre-loaded content, and splices it into the live stream based on detected markers, ensuring smooth transitions and customized content delivery during live events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If targeted content is inserted into live broadcast streams, then viewer engagement and advertising revenue are improved, but insertion timing and duration become uncertain leading to dead air and abrupt cutoffs
Solution Approach 1:
The system performs preliminary actions by buffering targeted content ahead of time and pre-positioning it in the playback buffer. When a content break is detected in the live stream, the buffered content is already ready for immediate insertion, eliminating dead air and ensuring smooth transitions without waiting for real-time content retrieval.
Solution Approach 2:
The system uses feedback mechanisms through content break markers embedded in the live stream that provide real-time information about upcoming content breaks. This feedback allows the media player to proactively load and buffer targeted content before the actual break occurs, enabling precise timing and avoiding abrupt cutoffs.
2Speed
If real-time playback speed is increased to maintain live broadcast freshness, then content relevance is improved, but targeted content customization opportunities are reduced
Solution Approach 1:
The system performs preliminary content selection and buffering actions during periods when the live stream is playing at normal speed. By anticipating content breaks and pre-loading customized content in advance, the system maintains the ability to provide highly customized targeted content even when the overall playback speed needs to be increased to preserve live broadcast freshness.
3Adaptability or versatility
If targeted content breaks are extended to allow more customization, then content relevance is improved, but broadcast timing flexibility is reduced
Solution Approach 1:
The system uses preliminary buffering of targeted content to decouple the customization process from the actual playback timing. Content can be prepared and customized in advance during buffer accumulation periods, then inserted at optimal moments when the live stream creates natural breaks. This allows extensive customization without being constrained by fixed break durations, as the buffered content can be inserted whenever a suitable timing opportunity arises.
Data Source
AI summary
The disclosed computer-implemented methods and systems can splice targeted content such as advertisements into a live stream of a real-time event. For example, the methods and systems discussed herein determine targeted content items for splicing into a live stream by generating a computing model of targeted content recommendations. In one or more examples, the computing model generates targeted content recommendations that are specific to a length of a targeted content break, the viewer of the live stream, and the player where the live stream is being viewed. The systems and methods discussed herein further determine the placement and duration of targeted content breaks based on signals and markers that are inserted into the live stream. Various other methods, systems, and computer-readable media are also disclosed.