Automatic Parameter Allocation for Multi-Effector Musical Instruments
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Solution Overview
Problem
Users of multi-effectors in electronic musical instruments face a burden in manually allocating effect parameters to operation elements, requiring significant thought and effort to set up desired combinations of sound effects during musical performance.
Innovation Solution
An effect adding apparatus that automatically assigns parameters to operation elements based on the significance of each parameter, using a processor to determine the most appropriate parameters for slider controllers by comparing significance values across multiple effects and applying rules for prioritization and pairing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually allocate effect parameters to operation elements one by one, then precise control over each parameter is achieved, but the complexity of operation and time required increase significantly
Solution Approach 1:
The system automatically performs parameter allocation to operation elements based on significance data without requiring manual user intervention. The processor autonomously determines which parameters to assign to which operation elements, allowing the system to serve itself rather than requiring the user to manually configure each parameter assignment.
Solution Approach 2:
The system pre-calculates and stores significance data for multiple effects before the user needs to perform any allocation. This preliminary preparation of parameter importance information enables rapid automatic assignment when the user selects effects, eliminating the need for time-consuming manual allocation during performance setup.
2Adaptability or versatility
If multiple effects with multiple parameters are combined, then the versatility and sound combination capability are improved, but the complexity of parameter management increases
Solution Approach 1:
The system introduces significance data as an intermediary layer between the multiple effect parameters and the operation elements. This intermediary information structure helps manage the complexity by providing a standardized way to evaluate and compare parameters across different effects, making it easier to automatically allocate them to appropriate operation elements.
Solution Approach 2:
The system changes the state of parameter management by transitioning from manual user-driven allocation to automatic processor-driven allocation based on significance values. This parameter change in the control method reduces the perceived complexity for users while maintaining the ability to handle multiple effects with multiple parameters.
3Ease of operation
If users are required to think about which parameter of which effect module to allocate to each operation element, then precise control is achieved, but the operational burden increases
Solution Approach 1:
The system performs the cognitively demanding task of parameter selection and allocation automatically, freeing the user from the burden of thinking about which parameters to assign where. The processor serves itself by making intelligent allocation decisions based on pre-stored significance data, eliminating the need for user cognitive effort in this aspect.
Solution Approach 2:
The system replaces the mechanical cognitive process of user decision-making with an automated information processing system. Instead of the user's brain analyzing and deciding parameter allocations, the processor automatically performs this function using stored significance data, substituting human cognitive effort with machine computation.
Data Source
AI summary
An effect adding apparatus includes: at least one first operation element on which a first user operation is performed; a plurality of second operation elements on which a second user operation is performed after the first user operation; and at least one processor, in which the at least one processor determines two or more effects including at least a first effect and a second effect, from a plurality of effects in which each of the effects is associated with a plurality of parameters, based on the first user operation on the at least one first operation element, and determines a parameter associated with each of the plurality of second operation elements, based on data indicating significance of each of a plurality of first parameters associated with the first effect determined and data indicating significance of each of a plurality of second parameters associated with the second effect determined.


