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MotionFlow is a web application that combines MediaPipe hand tracking with neural network harmony generation, allowing users to control pitch and volume in real time via gestures to create unique musical experiences.
Section 01
MotionFlow is a web application that combines MediaPipe hand tracking with neural network harmony generation. Users can control pitch and volume in real time via gestures to create unique musical experiences. This project aims to make music creation intuitive, eliminating the need for traditional instrument skills, and demonstrates new possibilities for human-computer interaction in artistic expression.
Section 02
Section 03
MotionFlow uses MediaPipe Hands to achieve low-latency hand tracking, distinguishing between the dominant hand and non-dominant hand:
Section 04
Neural Network Harmony Generation: The core highlight is the real-time four-part harmony generation feature. Through a neural network model, harmonious layers are generated based on gesture positions, allowing users without music theory knowledge to create pleasant harmonies. Audio Synthesis Engine: Built using the Web Audio API, it includes formant filtering technology (which imitates the physical characteristics of human voice to produce warm tones). Audio processing is executed in background threads to ensure 60FPS smoothness of the main interface.
Section 05
MotionFlow represents the future direction of accessible music creation. Its applicable groups include:
Section 06
MotionFlow successfully integrates computer vision, machine learning, and audio synthesis technologies, proving the potential of browser-based AI applications and the prospects of gesture interaction in the field of music creation. The project uses the GPLv3 open-source license, and the online demo can be accessed at: https://motionwavebydeepanshi.vercel.app, providing an excellent reference implementation for developers exploring new paradigms of human-computer interaction.
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