EEG-to-Melody Matching via Musical Probability Map
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Solution Overview
Problem
Non-professionals face difficulties in creating music without knowledge or skills in music composition or instrumentation, as existing technologies do not effectively assist in translating brain wave signals into musical melodies.
Innovation Solution
An electronic device and method that match musical imaginary electroencephalogram (EEG) with a melody by identifying key points in brain wave segments and compensating pitch values based on a musical probability map, considering harmonic and melodic progressions, to generate a natural and intuitive musical output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pitch values are classified based on key points of brain wave segments, then the matching accuracy between EEG and melody improves, but the naturalness and musicality of the generated melody deteriorates
Solution Approach 1:
The system uses a musical probability map that provides feedback by comparing classified pitch values against statistical patterns of natural music. The map contains probability information about which pitch values are likely to occur next based on harmonic and melodic progression rules, allowing the system to adjust and refine pitch assignments to produce more natural-sounding melodies while maintaining accurate EEG-to-pitch correspondence
Solution Approach 2:
The system changes parameters by introducing probabilistic adjustments to pitch values based on musical context. Instead of directly mapping brain wave key points to fixed pitch values, the system modifies pitch assignments according to the musical probability map, which considers harmonic progression, melodic patterns, and statistical frequency of pitch occurrences in natural music, thereby preserving both matching accuracy and musical naturalness
2Productivity
If brain wave segments are directly mapped to pitch values without musical context, then the processing speed increases, but the quality and naturalness of the generated music deteriorates
Solution Approach 1:
The system performs preliminary action by pre-computing and storing a musical probability map that contains statistical patterns of pitch values based on harmonic and melodic progression from a large dataset of music. This pre-computed knowledge base allows the system to quickly reference appropriate pitch values during real-time EEG processing, maintaining high processing speed while ensuring musically natural output through informed pitch selection
3Reliability
If a comprehensive musical probability map considering harmony and melodic progression is used, then the naturalness of generated melody improves, but the device complexity increases
Solution Approach 1:
The system uses copying by creating a simplified probabilistic model (musical probability map) that captures essential patterns of natural music without requiring the full complexity of musical theory processing. The map stores pre-analyzed statistical patterns of pitch, harmony, and melody from existing music, allowing the system to replicate natural musical characteristics through probability-based selection rather than complex real-time analysis
Data Source
AI summary
A method, performed by an electronic device, of matching a musical imaginary electroencephalogram (EEG) with a melody includes obtaining an EEG generated by imagining music from a user, obtaining at least one brain wave segment from the EEG, identifying key points included in the at least one brain wave segment, matching a pitch value to each of the at least one brain wave segment based on the identified key points, and compensating for the pitch value matching the at least one brain wave segment based on a musical probability map.