Transcript Paragraph Segmentation for Video Editing
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Solution Overview
Problem
Conventional video editing is tedious, challenging, and often beyond the skill level of many users due to its time-based nature and lack of intuitive interaction modalities.
Innovation Solution
The use of transcript interactions for video segment selection and editing, including face-aware speaker diarization, music-aware speaker diarization, and transcript paragraph segmentation, to facilitate text-based editing of audio and video assets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional time-based video editing interface is used, then video editing functionality is provided, but the editing process is tedious and challenging for users
Solution Approach 1:
The patent introduces a transcript as an intermediary layer between the user and the video content. Instead of directly manipulating video frames or timecodes, users interact with the transcript text to select and edit video segments. The system automatically maps transcript selections to corresponding video time ranges, eliminating the need for users to understand complex video editing timelines while maintaining precise editing control.
Solution Approach 2:
The patent replaces the mechanical interaction of dragging sliders and adjusting timecodes with text-based selection. Users can select video segments by simply clicking or highlighting text in the transcript, which automatically translates to the corresponding video time range. This substitution of mechanical time-based controls with text-based selection significantly simplifies the editing process.
2Ease of operation
If transcript-based video selection is implemented, then ease of operation is improved, but additional processing steps are required
Solution Approach 1:
The system performs preliminary actions by automatically generating and synchronizing the transcript with the video content before the user begins editing. The transcript is pre-aligned with video timecodes, and speaker diarization is pre-computed, so that when users select text, the corresponding video segments are immediately identified without requiring additional real-time processing.
Solution Approach 2:
The system makes itself serviceable by automatically handling the complex mapping between transcript text and video time ranges. When a user selects text in the transcript, the system self-service computes the corresponding video segment boundaries and performs the selection without requiring user intervention or complex manual configuration.
3Measurement precision
If speaker diarization is applied, then speaker identification accuracy is improved, but processing time increases
Solution Approach 1:
Speaker diarization is performed as a preliminary action during the video ingestion and transcript generation phase, rather than during user interaction. The system pre-computes speaker segments and associates them with transcript text, so that speaker identification is completed before the user begins editing, eliminating the need for real-time processing during the editing workflow.
Data Source
AI summary
Embodiments of the present invention provide systems, methods, and computer storage media for segmenting a transcript into paragraphs. In an example embodiment, a transcript is segmented to start a new paragraph whenever there is a change in speaker and/or a long pause in speech. If any remaining paragraphs are longer than a designated length or duration (e.g., 50 or 100 words), each of those paragraphs is segmented using dynamic programming to minimize a cost function that penalizes candidate paragraphs based on divergence from a target paragraph length and/or that rewards candidate paragraphs that group semantically similar sentences. As such, the transcript is visualized, segmented at the identified paragraphs.