{"ID":2876953,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.00106","arxiv_id":"2509.00106","title":"Quantum-Enhanced Analysis and Grading of Vocal Performance","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.","short_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...","url_abs":"https://arxiv.org/abs/2509.00106","url_pdf":"https://arxiv.org/pdf/2509.00106v1","authors":"[\"Rohan Agarwal\"]","published":"2025-08-28T01:34:33Z","proceeding":"eess.AS","tasks":"[\"eess.AS\",\"cs.SD\"]","methods":"[\"Transformer\"]","has_code":false}