Automated Media Stream Curation via Audio Cue Analysis
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Solution Overview
Problem
Users face challenges in efficiently locating and processing interesting segments within lengthy video or audio recordings, as conventional methods require time-consuming review and are complex to navigate.
Innovation Solution
A method that automates media stream curation by analyzing verbal and non-verbal audio cues from a separate audio track recorded contemporaneously with the media stream, using portable communication devices to detect timestamps and metadata, allowing for the extraction and editing of curated clips.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually review and scroll through entire video or audio recordings to locate interesting segments, then they can identify portions of particular interest, but the process becomes time-consuming and burdensome
Solution Approach 1:
The patent replaces the manual mechanical review process with an automated audio analysis system. The system uses audio cue detection algorithms to automatically identify segments containing speech, non-speech cues, and transitions, eliminating the need for users to manually scroll through recordings while maintaining accurate identification of interesting portions.
Solution Approach 2:
The system enables the recording itself to identify its own interesting segments through automated audio analysis. By detecting audio cues intrinsic to the recording content, the system allows the media to self-identify relevant portions without external human intervention, significantly reducing processing time while maintaining precision.
2Productivity
If users process large amounts of video or audio recordings to obtain useful portions, then they can extract valuable content, but the complexity of navigation and processing increases
Solution Approach 1:
The patent segments the processing task into distinct audio cue types (speech, non-speech cues, transitions) and processes each type separately using specialized detection algorithms. This segmentation simplifies the overall system complexity by breaking down the complex navigation task into manageable, independent detection modules that can be executed efficiently.
Solution Approach 2:
The system introduces an intermediary audio analysis layer between the raw recording and the user. This intermediary process automatically identifies and marks interesting segments based on audio cues, serving as a mediator that translates large amounts of raw media into organized, easily navigable highlighted portions, thereby increasing productivity without proportionally increasing user-facing complexity.
3Measurement precision
If conventional methods are used to review recordings, then users can locate interesting segments, but the ease of operation deteriorates due to time-consuming and burdensome processes
Solution Approach 1:
The patent replaces the manual navigation mechanics with automated audio-driven segment identification. The system analyzes audio cues to automatically locate and mark interesting segments, preserving the precision of segment identification while dramatically improving ease of operation by eliminating the need for users to manually navigate through entire recordings.
Data Source
AI summary
A method to automate media stream curation implements verbal and non-verbal audio cue analysis of an audio track recorded contemporaneously with a media stream. The media stream may be a video stream or an audio stream. The audio track is recorded contemporaneously with the media stream using a recording device separate from the media recording device used to record the media stream. Audio cue analysis of the audio track is performed to detect for audio cues which indicate the locations or timestamps associated with elements of interest. The identified elements of interest are then used to extract segments of the media stream to form a curated media stream containing clips associated with the elements of interest.