Support Function Recommending System for Electronic Musical Instruments

Solution Overview

Problem

Users of electronic musical instruments with multiple support functions struggle to determine which function is most effective for improving their playing technique, as existing technologies do not provide personalized recommendations based on user data and preferences.

Innovation Solution

A support function recommending system that collects and analyzes user data on proficiency levels and support function usage, comparing this information across multiple users to determine the most effective support functions for improving playing technique, and provides personalized recommendations to users based on this analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If multiple support functions are provided on electronic pianos to satisfy various user preferences, then the versatility and adaptability of the system is improved, but the device complexity increases and users struggle to determine which function is most effective for them

Engineering Contradiction:

Improvesupport function varietyVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system automatically analyzes user performance data and proficiency levels to determine the most effective support functions, eliminating the need for users to manually evaluate multiple functions. The apparatus self-determines recommendations based on objective data rather than requiring user judgment.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system continuously monitors user performance data and proficiency levels, using this feedback to dynamically determine the most effective support functions. This closed-loop approach allows the system to adapt recommendations based on actual user progress and outcomes.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If multiple support functions are provided to meet diverse user needs, then the adaptability is improved, but the ease of operation deteriorates as users cannot determine which function to use

Engineering Contradiction:

Improvesupport function varietyVSAvoiduser operation simplicity

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system automatically analyzes user performance data and proficiency levels to determine the most effective support functions, eliminating the need for users to manually evaluate multiple functions. The apparatus self-determines recommendations based on objective data rather than requiring user judgment.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The recommending apparatus acts as an intermediary between the user and the multiple support functions, filtering and selecting the most appropriate function based on user data. This mediator simplifies the user's task by presenting only the most relevant recommendation rather than requiring them to navigate multiple options.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Ease of operation

If the system provides personalized support function recommendations based on user data analysis, then the ease of operation is improved, but the device complexity and processing requirements increase

Engineering Contradiction:

Improveuser operation simplicityVSAvoidsystem complexity

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system automatically analyzes user performance data and proficiency levels to determine the most effective support functions, eliminating the need for users to manually evaluate multiple functions. The apparatus self-determines recommendations based on objective data rather than requiring user judgment.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system pre-analyzes user performance data and proficiency levels before providing recommendations, performing the complex analysis work in advance. This preliminary processing prepares the data structure needed for recommendation generation, reducing the computational burden during the actual recommendation delivery.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS8809664B2Support function recommending apparatus, a support function recommending method, a support function recommending system, and a recording medium

Publication Date: 2014.08.19 CASIO COMPUTER CO LTD

AI summary

Plural electronic musical instruments 2 obtain proficiency level related information, that includes items such as usage amounts of plural support functions which are used by a user in performing a playing practice of a practice piece during a period from a previous practice to the last practice and a proficiency level of a playing technique of a practice piece, and supply the information to a server 1. The server stores the received proficiency level related information in a database 14. Upon receipt of the information, a controlling unit 12 of the server 1 sends back the electronic musical instrument 2 information indicating the support function most suitable for practicing the practice piece determined on the basis of the received information and a series of information stored in the database containing the proficiency level related information including the item of the proficiency level corresponding to an aimed level.