This paper introduces Chord Colourizer, a near real-time system that detects the musical key of an audio signal and visually represents it through a novel graphical user interface (GUI). The system assigns colours to musical notes based on Isaac Newton's original colour wheel, preserving historical links between pitch and hue, and also integrates an Arduino-controlled LED display using 3D-printed star-shaped diffusers to offer a physical ambient media representation. The method employs Constant-Q Transform (CQT) chroma features for chord estimation and visualization, followed by threshold-based filtering and tonal enhancement to isolate the root, third, and fifth. A confidence score is computed for each detection to ensure reliability, and only chords with moderate to very strong certainty are visualized. The graphical interface dynamically updates a colour-coded keyboard layout, while the LED display provides the same colour information via spatial feedback. This multi-modal system enhances user interaction with harmonic content, offering innovative possibilities for education and artistic performance. Limitations include slight latency and the inability to detect extended chords, which future development will aim to address through refined filtering, adaptive thresholds, and support for more complex harmonies such as sevenths and augmented chords. Future work will also explore integration with alternative visualization styles, and the comparison of audio analysis libraries to improve detection speed and precision. Plans also include formal user testing to evaluate perception, usability, and cross-cultural interpretations of colour-pitch mappings.
翻译:本文介绍了和弦着色器(Chord Colourizer),一种近实时系统,能够检测音频信号的音乐调性并通过新颖的图形用户界面(GUI)进行可视化呈现。该系统基于艾萨克·牛顿的原始色轮为音符分配颜色,保留了音高与色调之间的历史联系,并集成了由Arduino控制的LED显示屏(采用3D打印的星形漫射器),以提供物理环境媒体表征。该方法采用恒定Q变换(CQT)色度特征进行和弦估计与可视化,随后通过基于阈值的滤波和调性增强来分离根音、三音和五音。每次检测均计算置信度分数以确保可靠性,仅对具有中等至极强确定性的和弦进行可视化。图形界面动态更新颜色编码的键盘布局,而LED显示屏则通过空间反馈提供相同的色彩信息。这种多模态系统增强了用户与和声内容的交互,为教育和艺术表演提供了创新可能性。局限性包括轻微延迟以及无法检测扩展和弦,未来开发将通过优化滤波、自适应阈值和支持更复杂的和声(如七和弦与增和弦)来解决这些问题。未来工作还将探索与替代可视化风格的整合,并比较音频分析库以提升检测速度与精度。计划还包括开展正式用户测试,以评估颜色-音高映射的感知效果、可用性及跨文化解读。