Dynamic Content Description Library for TTS Optimization
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Solution Overview
Problem
Existing mobile applications face inefficiencies in processing visual component descriptions for visually impaired users, as text-to-speech algorithms struggle with acronyms and abbreviations, and current methods require significant computational resources for dynamic updates, leading to increased latency and resource consumption.
Innovation Solution
A dynamic library that modifies content descriptions on the fly, optimizing text for audio signal generation by performing targeted character replacements and adding contextual information, reducing computational and network resource usage by updating the library once for multiple applications rather than re-compiling each application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If text-to-speech algorithms process acronyms and abbreviations directly, then processing speed is maintained, but accuracy of audio output deteriorates
Solution Approach 1:
The system performs preliminary expansion of acronyms and abbreviations into their full forms before text-to-speech processing. A library stores pre-defined acronym-to-full-form mappings, and the system proactively replaces abbreviated terms with their complete expansions prior to audio generation, ensuring accurate pronunciation while maintaining efficient processing through pre-computed transformations.
Solution Approach 2:
The patent introduces an intermediary processing layer between the input text and text-to-speech algorithm. This intermediary component acts as a mediator that detects acronyms and abbreviations, consults a reference library, performs expansions, and outputs modified text to the TTS engine. This mediator resolves the contradiction by handling the complex expansion task separately, allowing the core TTS algorithm to process expanded terms efficiently while achieving accurate audio output.
2Measurement precision
If content descriptions are dynamically updated for each application, then customization and accuracy improve, but computational resources and processing time increase
Solution Approach 1:
The patent implements a universal acronym and abbreviation expansion library that serves multiple mobile applications simultaneously. Instead of maintaining separate expansion databases for each application, the system uses a single shared library that can be queried by any application needing acronym expansion. This universal approach reduces redundant storage and computational overhead while providing customized expansion services to multiple applications, thereby lowering overall resource consumption while maintaining accuracy.
3Measurement precision
If applications are re-compiled for each update, then content description accuracy improves, but development time and complexity increase
Solution Approach 1:
The patent segments the acronym expansion functionality into a separate, independent module or library that can be updated without affecting the core application code. This segmentation allows the expansion library to be maintained, modified, and updated independently through simple file updates rather than requiring full application re-compilation. Developers can update acronym definitions and expansion rules in isolation, reducing development complexity while maintaining accurate content descriptions.
Data Source
AI summary
In some implementations, a mobile application may receive at least one string included in at least one content description associated with at least one visual component of a screen generated by a mobile application. The mobile application may apply a function to the at least one string, wherein the function performs a targeted replacement of characters included in the at least one string based on at least one optimization associated with a text-to-speech algorithm. Accordingly, the mobile application may receive output from the function that includes at least one modified string based on the at least one string and generate an audio signal, based on the at least one modified string, using the text-to-speech algorithm.