# Quantum-Enhanced Analysis and Grading of Vocal Performance

## TL;DR

This paper introduces QuantumMelody, a hybrid quantum-classical system for objective singing assessment that achieves higher agreement with experts than classical methods, demonstrating feasibility for interpretable, automated vocal evaluation.

## Contribution

The paper presents a novel quantum-enhanced approach for singing assessment, combining quantum circuits with classical embeddings to improve grading accuracy.

## Key findings

- Achieves 74.29% agreement with expert graders
- Outperforms classical baseline by +12.86 points
- Operates efficiently on standard laptops

## Abstract

We present QuantumMelody, a hybrid quantum-classical method for objective singing assessment. Grouped vocal features (pitch stability, dynamics, timbre) are encoded into a small simulated quantum circuit; all nine qubits are initialized with a Hadamard on each qubit and then receive Rx, Ry, and Rz rotations, with intra- and cross-group entanglement. The circuit measurement probabilities are fused with spectrogram transformer embeddings to estimate a grade on labels 2-5 and to surface technique-level feedback. On 168 labeled 20 second excerpts, the hybrid reaches 74.29% agreement with expert graders, a +12.86 point gain over a classical-features baseline. Processing is sub-minute per recording on a laptop-class Qiskit simulator; we do not claim hardware speedups. This is a feasibility step toward interpretable, objective singing assessment in applied audio signal processing.