Word-Timed Subtitle Animation for Automatic Multimedia Editing
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Solution Overview
Problem
Existing subtitle editing methods are inefficient and inconvenient, requiring manual adjustment and segmentation of subtitle texts, especially for achieving specific animation effects, which is time-consuming and cumbersome, particularly on mobile devices.
Innovation Solution
A subtitle processing method that utilizes speech recognition to generate subtitle texts with timestamp information, matches these elements with corresponding multimedia material fragments, and synthesizes them to create an animation effect where text appears word by word, allowing for automatic generation and easy editing of dynamic subtitles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple separate models are trained for different subtitle processing tasks, then each task can be optimized independently, but the overall system complexity increases and inference time is extended
Solution Approach 1:
The patent combines multiple separate subtitle processing models (subtitle generation model, subtitle translation model, subtitle correction model) into a single unified model. This unified model accepts video input and simultaneously performs all subtitle processing tasks, reducing system complexity while maintaining processing accuracy through integrated multi-task learning
2Measurement precision
If multiple separate models are trained for different subtitle processing tasks, then each task can be optimized independently, but the inference time is extended
Solution Approach 1:
The unified model processes all subtitle tasks in a single inference pass rather than sequentially executing multiple separate models. This integration significantly reduces inference time while maintaining the accuracy benefits of specialized processing for each subtitle task
3Device complexity
If a unified model is used for all subtitle processing tasks, then system complexity is reduced and inference time is shortened, but the training difficulty increases
Solution Approach 1:
The patent segments the training process into distinct stages: first training the subtitle generation model with video-caption pairs, then fine-tuning with subtitle translation and correction tasks. This staged segmentation approach makes the complex unified model training more manageable and easier to implement
Solution Approach 2:
The patent performs preliminary training of the base subtitle generation model before adapting it for multiple tasks. This preliminary action establishes a solid foundation that simplifies subsequent multi-task fine-tuning and reduces overall training difficulty
Data Source
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AI summary
The present disclosure relates to a subtitle processing method and apparatus, wherein the method includes: performing, in a process of editing multimedia material, speech recognition on an audio corresponding to the multimedia material to obtain a subtitle text corresponding to the audio and timestamp information of audio fragments corresponding to respective text elements in the subtitle text; determining material fragments in the multimedia material fragment respectively matching with the text elements according to the timestamp information of the audio fragments respectively corresponding to the respective text elements; and synthesizing the respective text elements respectively with material fragments in a matching time period, to obtain a target multimedia material with an animation effect in which the subtitle text jumps out word by word. The scheme of the present can achieve a subtitle animation effect in which a subtitle text corresponding to a certain word appears as the certain word is spoken. In addition, automatic generation of a dynamic subtitle can be implemented by inputting instructions by a user, and the user's operation is simple, which is beneficial to improving user's experience.