Processor-Based Musical Performance Visualization System
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Solution Overview
Problem
Existing systems for synchronizing image objects with musical performances primarily focus on dynamic appearance without effectively integrating pitch data to enhance the visual representation of musical compositions.
Innovation Solution
A processor-based method that receives performance data, determines the key (major or minor) from pitch data, and selects corresponding image types (flowers or plants) for display, adjusting size and color based on velocity values and scoring results, to create a visual representation of the musical composition in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a character merely dynamically appears during the performance, then the system is simple to implement, but the visual representation lacks depth and fails to convey pitch relationships
Solution Approach 1:
The system segments the visual representation into multiple image objects (first-type images for pitch, second-type images for chords) that can be independently selected and displayed based on different musical parameters, allowing comprehensive pitch relationship visualization without overwhelming system complexity
Solution Approach 2:
The system adds a visual dimension to musical performance by mapping pitch data to spatial positions and selecting images from multiple dimensions (type, size, color), transforming abstract pitch relationships into tangible visual representations that convey musical structure
2Loss of information
If multiple image parameters (type, size, color) are adjusted based on performance data, then the visual feedback becomes richer and more informative, but the processing complexity increases
Solution Approach 1:
The system applies different image parameters (type, size, color) to different aspects of performance data (pitch, velocity, scoring), where each parameter locally represents a specific musical attribute, enabling rich visual feedback through targeted parameter adjustment rather than uniform processing
Solution Approach 2:
The system changes multiple image parameters (type selection from first-type images, size scaling, color modification) based on performance data variables (pitch data, velocity values, scoring results), transforming musical performance into a multi-dimensional visual representation that preserves comprehensive performance information
3Loss of information
If the system displays images reflecting both melody and chord progressions, then the musical composition representation becomes more complete, but the selection and display complexity increases
Solution Approach 1:
The system merges melody representation (first-type images based on pitch data) and chord progression representation (second-type images based on chord data) into a unified visual display, where both types of images coexist and interact to convey the complete compositional structure
Solution Approach 2:
The image selection system serves multiple functions simultaneously: selecting first-type images for pitch visualization, second-type images for chord visualization, adjusting sizes for emphasis, and modifying colors for differentiation, all through a unified selection process that handles diverse musical information
Data Source
AI summary
A method implemented by a processor includesreceiving performance data including pitch data;determining, based on the pitch data that is included in the received performance data, a key among a plurality of keys;selecting, based on the determined key and the pitch data, a first-type image from among a plurality of first-type images; anddisplaying the selected first-type image.