Video Script Generation With Timestamps for Easier Editing
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Solution Overview
Problem
The creation of high-quality video scripts for user-generated videos is challenging due to the high requirements for video authors and the complexity of script creation, which increases the difficulty of video editing.
Innovation Solution
A video editing method that utilizes a pre-trained script generation model to automatically generate a video script by mapping video frames to a text feature space, incorporating a timestamp, and adding the script to the original video to produce a target video.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a script generation model is used to automatically generate video scripts, then the difficulty of video creation is reduced and the process is simplified, but the quality and attractiveness of the generated scripts may not meet the high standards required for high-quality video content
Solution Approach 1:
The script generation model is pre-trained in advance using a large number of video samples and their corresponding high-quality scripts. This preliminary training action enables the model to learn effective script writing patterns and styles before actual video script generation, ensuring both ease of operation during use and high reliability of generated scripts.
Solution Approach 2:
The model is trained using video samples with known high-quality scripts as feedback targets. During training, the model receives feedback by comparing its generated scripts against the ground truth scripts from the training data, allowing it to continuously improve its script generation quality while maintaining automated operation.
2Reliability
If high-quality video scripts are created manually to increase video attractiveness and spread, then the video quality is improved, but the complexity and difficulty of video creation increases
Solution Approach 1:
The script generation model performs self-service by automatically generating video scripts without requiring manual intervention from video creators. The model independently processes video input and produces scripts, eliminating the need for creators to manually write scripts while maintaining high video quality through the model's learned capabilities.
Solution Approach 2:
The manual mechanical process of script writing by video creators is replaced with an automated computational system. The script generation model substitutes the human creative process with an algorithmic approach that analyzes video content and generates scripts automatically, reducing creation complexity while preserving quality.
3Reliability
If manual script creation is required to ensure script quality, then the script attractiveness is improved, but the time and effort required for video editing increases
Solution Approach 1:
The script generation model enables continuous automated script creation without interruption or manual intervention. Once the model is trained, it can continuously generate scripts for multiple videos in sequence, eliminating the time-consuming manual script writing process while maintaining consistent quality across all generated scripts.
Data Source
AI summary
Embodiments of the present disclosure provide a video editing method, apparatus, device, medium and program product. The method includes: inputting an original video into a script generation model that is pre-trained; generating, by the script generation model, a video feature sequence according to video frames in the original video, mapping the video feature sequence to a text feature space of the script generation mode, and obtaining a video mapping feature sequence; generating, by the script generation model, a second video script of the original video based on the video mapping feature sequence, wherein the second video script includes a timestamp; adding the second video script to the original video according to the timestamp to obtain a target video