Style-Aware AI Text-Speech Conversion Engine
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Solution Overview
Problem
Conventional speech-to-text and text-to-speech services fail to reflect various speech and text styles, resulting in uniform conversions for all users, lacking personalization and realism.
Innovation Solution
An artificial intelligence apparatus and method that determines the style of inputted text or speech, using corresponding TTS or STT engines to generate output in the specific style of the user, allowing for personalized and realistic conversions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a predetermined STT engine or TTS engine is used for speech-to-text or text-to-speech conversion, then the conversion service is simple to implement, but it cannot reflect various speech styles and text styles, resulting in uniform conversions for all users
Solution Approach 1:
The patent segments the conversion system into multiple style-specific engines (e.g., news style STT, fairy tale style TTS, entertainment style TTS). Each engine is specialized for a particular style, allowing the system to handle diverse speech and text styles without requiring a single complex universal engine. This segmentation enables style adaptation while keeping individual engine components relatively simple.
Solution Approach 2:
The patent creates a universal conversion platform that can perform multiple functions by selecting appropriate style-specific engines based on the input. The system architecture allows a single platform to handle various speech-to-text and text-to-speech conversions across different styles, making the overall system multi-functional while maintaining simplicity through engine selection rather than complex internal adaptation.
2Adaptability or versatility
If conventional STT or TTS engines are used, then the conversion process is fast and efficient, but the output lacks personalization and realism as all conversions follow the same style
Solution Approach 1:
The patent applies preliminary action by pre-training multiple style-specific STT and TTS engines on different speech and text styles before actual conversion operations. Styles such as news, fairy tales, and entertainment content are preprocessed into dedicated engine configurations. This allows the system to quickly select and apply the appropriate pre-configured engine during conversion, maintaining high productivity while achieving personalization without real-time style analysis or adaptation overhead.
3Manufacturing precision
If multiple style-specific engines are implemented, then various speech and text styles can be accurately reflected, but the system complexity and resource requirements increase
Solution Approach 1:
The patent uses copying by creating multiple style-specific engine instances (copies) of the base STT and TTS architecture, each trained on different style data. Rather than developing fundamentally different engine types for each style, the system copies the proven engine architecture and adapts it to specific styles through training data, achieving high conversion accuracy for various styles while reusing the same underlying technical framework.
Data Source
AI summary
According to an embodiment of the present invention, there is provided an artificial intelligence (AI) apparatus for mutually converting a text and a speech, including: a memory configured to store a plurality of Text-To-Speech (TTS) engines; and a processor configured to: obtain image data containing a text, determine a speech style corresponding to the text, generate a speech corresponding to the text by using a TTS engine corresponding to the determined speech style among the plurality of TTS engines, and output the generated speech.