
QuantumMelody
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Can quantum-inspired models be used to analyze and compare vocal performance by encoding musical features related to pitch, dynamics, and timbre?
QuantumMelody explores the use of quantum and quantum-inspired computational models to analyze vocal music performance. The project encodes musical features such as pitch stability, timing, dynamics, and timbral characteristics into structured quantum circuits, enabling comparative analysis between performers or between a student and reference performance. By grouping features and leveraging entanglement within feature sets, the approach aims to capture relationships that are difficult to represent with classical models alone. The work serves as an exploratory investigation into novel representations for music analysis and evaluation.
Research at a Glance
Primary Methods
Quantum feature encoding; audio signal analysis; circuit-based modeling; comparative evaluation.
Data Sources
Extracted audio features from vocal recordings; pitch, timing, dynamic, and timbral descriptors derived from signal processing pipelines.
Outputs
Quantum circuit designs; feature encoding strategies; comparative performance metrics; experimental evaluation results.
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