Chord Detection Apparatus for Real-Time Musical Accompaniment
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Solution Overview
Problem
Existing electronic musical instruments struggle to detect chords musically related to real-time performance data, as they cannot account for future notes, leading to repetitive chord progressions and a lack of variety in musical accompaniment.
Innovation Solution
A chord detection apparatus and method that acquires performance data, determines tonality information, and extracts chord candidates based on reference chords, allowing for the selection of chords that can follow the reference chord, including non-functional and interrupted cadence chords, to provide a variety of musically related chords during real-time performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If chord progression is extracted based on performance data input beforehand, then a chord progression musically well related to performance data can be extracted by taking account of performance tones subsequent to current performance tone, but if real-time performance data is used, then future performance tones are unknown and chord progression cannot be extracted musically well related to real-time performance
Solution Approach 1:
The system pre-acquires performance data before actual playback, allowing chord detection to consider both past and future notes. This preliminary data acquisition enables accurate chord progression extraction by analyzing the entire performance sequence in advance, then synchronizing chord changes with the performance timeline.
2Reliability
If predicted chord is extracted from chord progression database, then a chord progression musically related to performance data can be obtained, but the same chord progression frequently appears causing user fatigue
Solution Approach 1:
The system dynamically adjusts chord progression selection based on performance characteristics. It analyzes the acquired performance data to determine appropriate chord progressions that match the musical context, allowing the system to vary chord selections while maintaining musical coherence. This dynamic approach prevents repetitive progressions by adapting to the specific performance being played.
Solution Approach 2:
The system changes parameters such as chord timing, chord selection, and progression patterns based on performance data analysis. By modifying these parameters dynamically, the system generates diverse chord progressions that remain musically appropriate for the given performance, preventing user fatigue from repetitive patterns.
3Productivity
If chord detection considers only past performance tones, then real-time processing is possible, but chord progression cannot be musically well related to performance data
Solution Approach 1:
The system performs preliminary acquisition of performance data before actual chord detection and playback. This allows the system to analyze the entire performance sequence in advance, determining accurate chord progressions that consider both past and future notes, while maintaining real-time performance capability through pre-computed chord timing information.
Data Source
AI summary
A chord detection apparatus capable of detecting a wide variety of chords musically related to realtime performance. Degree name candidates each having a function that can come next are extracted in a first extraction process, degree name candidates corresponding to an interrupted cadence are extracted in a second extraction process, and degree name candidates corresponding to a non-functional chord progression technique are extracted in a third extraction process. The degree name candidates extracted in these extraction processes are developed into chord names according to a current tonality, and one of chords represented by the chord names is selected according to performance data and output to an automatic accompaniment apparatus for sound production.