Voice Instruction Analysis for Personalized Exercise Support
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Solution Overview
Problem
Existing technologies face challenges in providing effective voice support to individuals during exercises, as the effectiveness of voice instructions varies significantly among individuals.
Innovation Solution
An information processing method that analyzes the characteristics of voice instructions by associating changes in exercise state values with the characteristics of multiple voices transmitted to a target person, using correspondence information stored in the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If voice instructions are transmitted to support target person's exercise, then exercise support is provided, but effectiveness varies significantly among individuals
Solution Approach 1:
The system customizes voice instruction characteristics for each target person based on their individual attributes (age, gender, fitness level) and real-time exercise state. By analyzing correspondence information between voice characteristics and exercise state changes for each individual, the system adapts the voice support to match specific user needs, resolving the contradiction between providing effective support and accounting for individual variation
Solution Approach 2:
The system dynamically adjusts voice instruction parameters (tone, volume, timing, content) based on the target person's exercise state and individual characteristics. By changing voice parameters according to measured exercise state values and individual profiles, the system optimizes effectiveness for each user while maintaining adaptability across different individuals
2Reliability
If multiple voice characteristics are analyzed to personalize support, then individualized effectiveness is achieved, but system complexity increases
Solution Approach 1:
The system uses a unified analysis framework that processes multiple voice characteristics and exercise state parameters through a single correspondence information storage structure. This multi-functional approach allows the same system architecture to handle various voice attributes (tone, volume, timing) and exercise metrics simultaneously, achieving personalized support without proportionally increasing system complexity
Solution Approach 2:
The system automatically collects exercise state data from sensors and performs self-analysis by comparing voice characteristics against measured state changes. The target person's own exercise data serves as the basis for generating personalized voice instruction profiles, reducing the need for external configuration and simplifying the overall system complexity
Data Source
AI summary
Disclosed is an information processing method executed by an information processing device including a memory in which a program is stored and at least one processor that executes the program, the method including specifying, by the processor, a characteristic of a voice that induces a change in a state value based on correspondence information in which the change in the state value before and after each transmission timing of multiple voices transmitted to a target person in action is associated with a characteristic of each of the multiple voices, the state value representing an action state of the target person.