Automated Audio Description Timing Using Frame-to-Text Summaries
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Solution Overview
Problem
The creation of audio descriptions for video content is expensive and cumbersome, requiring skilled script writers and voice talent, and existing automated systems do not alleviate the need for skilled script writing or optimize the placement and phrasing of descriptive text.
Innovation Solution
An automated audio description system that uses an image-to-text model to generate textual descriptions of frames, identifies intervals and placement periods, and employs large language models to summarize descriptions for accurate audio generation, reducing the need for human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual audio description creation is used, then quality and accuracy of descriptions are improved, but cost and time consumption increase significantly
Solution Approach 1:
The patent replaces the manual mechanical process of scriptwriting and voice recording with an automated system that uses image-to-text models to generate descriptions and speech synthesis to produce audio. This substitution eliminates the need for human script writers and voice talent while maintaining description quality through AI-powered frame analysis and temporal alignment algorithms.
Solution Approach 2:
The system performs self-service by automatically analyzing video frames, generating textual descriptions, determining optimal placement periods, and synthesizing audio without requiring human intervention. The automated pipeline processes entire video content independently, generating audio descriptions that fit timing constraints and integrate with existing audio tracks.
2Manufacturing precision
If skilled script writers and voice talent are employed, then description accuracy and timing precision are improved, but production cost increases
Solution Approach 1:
The patent replaces skilled human professionals with automated AI systems. The image-to-text model generates accurate frame descriptions, the temporal alignment algorithm precisely determines placement timing, and speech synthesis produces the final audio. This eliminates dependency on skilled labor while maintaining high timing precision through computational algorithms.
Solution Approach 2:
The system creates digital copies of the description content through automated generation rather than relying on original human creations. The AI models generate textual descriptions that replicate the quality of human-written scripts, and speech synthesis creates audio copies that match professional voice talent, eliminating the need to pay skilled workers.
3Ease of manufacture
If automated systems are used to reduce cost, then production cost decreases, but the need for skilled script writing remains
Solution Approach 1:
The patent fully replaces the scriptwriting mechanical process with AI-powered image-to-text models that automatically generate descriptions from video frames. This complete substitution eliminates the need for skilled script writers entirely, achieving true automation in the description generation process.
Solution Approach 2:
The system achieves self-service automation where the entire audio description creation process occurs independently without human intervention. The automated pipeline handles frame analysis, description generation, timing determination, and audio synthesis, completely eliminating the need for skilled script writing expertise.
4Reliability
If iterative recording processes are used to optimize descriptions, then description effectiveness is improved, but time consumption and complexity increase
Solution Approach 1:
The patent replaces the iterative mechanical recording process with a single-pass automated generation system. The image-to-text model generates descriptions in one operation, and the speech synthesis system produces the final audio without requiring multiple recording sessions. This eliminates the complexity of iterative optimization while maintaining effectiveness through AI-powered generation.
Solution Approach 2:
The system performs preliminary actions by pre-processing video frames and generating all necessary descriptions and timing information before final audio synthesis. The automated pipeline analyzes content and determines placement periods in advance, eliminating the need for iterative adjustments and simplifying the overall process.
Data Source
AI summary
An audio description system includes a memory and a processor. The memory stores source media comprising frames positioned within the source media according to a time index. The processor is configured to generate, using an image-to-text model, a textual description of each frame; identify intervals within the time index, each interval encompassing one or more positions of one or more frames; identify placement periods within the time index, each placement period being temporally proximal to an interval; generate a summary description based on at least one textual description of at least one frame positioned within a selected interval temporally proximal to a placement period; and associate the summary description with the placement period.