Method and apparatus for generating differentiated oral prompts for learning
By generating personalized verbal prompts and utilizing a conditional language generation model combined with diagnostic and suggestion vectors, the problem of AI coaches lacking personalized communication is solved, thereby improving learning efficiency and interest.
JP2026511871APending Publication Date: 2026-04-14AGENCY FOR SCI TECH & RES
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Patent Information
- Application Number
- JP2025557242
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-03-30
- Filing Date
- 2024-03-27
- Publication Date
- 2026-04-14
AI Technical Summary
Technical Problem
Existing AI coaches lack personalized communication and cannot assess students' learning progress in real time, resulting in low learning efficiency. Furthermore, the information they provide lacks direct relevance, leading to a dull and frustrating learning process.
Method used
By generating personalized verbal cues, and utilizing a conditional language generation model that combines diagnostic and suggestion vectors, customized verbal feedback is produced, including emotional settings and adjustments to tone, rhythm, and volume, providing encouragement and guidance.
Benefits of technology
It improves the personalization and effectiveness of learning, reduces students' frustration, and increases their interest and efficiency in learning.
✦ Generated by Eureka AI based on patent content.
Abstract
A method and apparatus for generating one or more differentiated oral prompts for learning, the method comprising: presenting a learning task to a user on a display; receiving user feedback on the learning task; determining a diagnostic input based on the user feedback; performing a diagnosis on the diagnostic input using a prompt generation model to generate differentiated oral prompts and differentiated speech emphasis masks associated with the differentiated oral prompts; inputting the differentiated oral prompts and differentiated speech emphasis masks to a text-to-speech module having prosodic control so as to generate an audio signal for reading a differentiated oral prompt having the speech emphasis specified in the differentiated speech emphasis mask, wherein the differentiated speech emphasis mask includes data indicating prosodic control; and converting the audio signal to a format for reading a differentiated oral prompt having the specified speech emphasis via an audio device.
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