Generative Films Using Neural Visual Dubbing for Language Localization
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Solution Overview
Problem
The integration of visual dubbing technologies into the filmmaking pipeline is challenging due to the serial nature of tasks performed by post-production and localization houses, leading to inefficiencies and increased costs, especially when creating multiple language versions of films.
Innovation Solution
A computer-implemented method using neural networks to generate and edit animated representations of objects, allowing for interactive and iterative editing with real-time feedback, and a two-stage neural network approach for high-quality finalization, reducing the need for reshoots and simplifying the filmmaking process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If visual dubbing technologies are integrated into the existing filmmaking pipeline, then the quality and nuance of foreign language versions are improved, but the complexity of the production process increases and resource conflicts arise
Solution Approach 1:
The patent segments the visual dubbing process into distinct stages: (1) generating initial visual dubbing output using automated neural network technologies, (2) presenting this output for review, and (3) allowing iterative refinements. This segmentation enables quality improvement while managing complexity by breaking down the overall process into manageable components that can be handled by different specialists.
Solution Approach 2:
The patent introduces an intermediary review and refinement stage between automated visual dubbing generation and final delivery. This intermediary layer allows for quality control and nuance adjustment without requiring complete reshoots, thereby improving output quality while reducing the overall complexity compared to traditional reshoot approaches.
2Adaptability or versatility
If multiple language versions are created using conventional localization processes, then language diversity is achieved, but time consumption and resource expenditure increase significantly
Solution Approach 1:
The patent applies preliminary action by generating initial visual dubbing outputs for multiple language versions using automated neural network technologies before final review and refinement. This allows for rapid creation of multiple language variants, significantly reducing the time required compared to traditional post-production approaches where each language version requires separate recording and editing sessions.
Solution Approach 2:
The patent uses copying by creating synthesized visual representations of actors performing in different languages using neural networks trained on original performances. This allows multiple language versions to be generated by copying and transforming the original performance data, rather than requiring actual reshoots with different actors or language versions, thereby achieving language diversity without proportional increases in time and resources.
3Manufacturing precision
If reshoots are performed to modify actor performance aspects, then the quality of the film is improved, but costs and time consumption increase
Solution Approach 1:
The patent uses copying by creating synthesized visual representations of actors performing in different languages using neural networks trained on original performances. This allows multiple language versions to be generated by copying and transforming the original performance data, rather than requiring actual reshoots with different actors or language versions, thereby achieving language diversity without proportional increases in time and resources.
Solution Approach 2:
The patent replaces the mechanical system of physical reshoots with a neural network-based synthesis system. Instead of physically recasting actors or reperforming scenes, the system uses machine learning models to generate new visual performances by transforming existing performance data, thereby achieving performance modifications without the time and resource costs of actual reshoots.
4Adaptability or versatility
If secondary language actors record dialogue audio separately, then language localization is achieved, but the nuance and quality of the original film are lost
Solution Approach 1:
The patent uses copying by creating synthesized visual representations of actors performing in different languages using neural networks trained on original performances. This allows multiple language versions to be generated by copying and transforming the original performance data, rather than requiring actual reshoots with different actors or language versions, thereby achieving language diversity without proportional increases in time and resources.
Solution Approach 2:
The patent replaces the mechanical system of physical reshoots with a neural network-based synthesis system. Instead of physically recasting actors or reperforming scenes, the system uses machine learning models to generate new visual performances by transforming existing performance data, thereby achieving performance modifications without the time and resource costs of actual reshoots.
Data Source
AI summary
A computer implemented method includes receiving, from a remote system, object data comprising values of a set of adjustable parameters of a respective object representation model for each object of a plurality of objects and compositing data indicating at least a respective trajectory of each of the plurality of objects relative to a reference frame. The method includes processing the object data and the compositing data using the respective object representation models to generate output video data depicting a scene including an animated representation of each object of the plurality of objects following the respective trajectory relative to the reference frame. For each object of the plurality of objects, the respective object representation model comprises a respective neural network and is arranged to generate, using the respective neural network, animated representations of the object in which a geometry the object is controllable by the set of adjustable parameters.