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pith:FM3JGBCP

pith:2026:FM3JGBCPRYDFHK5RXYYSCVSC7N

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A Distribution Matching Approach to Neural Piano Transcription with Optimal Transport

Dichucheng Li, Kazuyoshi Yoshii, Raynaldi Lalang, Weixing Wei

Automatic piano transcription improves when framed as optimal transport between note distributions rather than frame-by-frame classification.

arxiv:2605.17405 v1 · 2026-05-17 · cs.SD · cs.MM

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Claims

C1strongest claim

This paper describes a novel paradigm that formalizes automatic piano transcription (APT) as an optimal transport (OT) problem, not as a frame-level multi-label binary classification problem. Our method learns to minimize the cost of transporting a predicted distribution of note events to the ground-truth distribution over time and frequency. The OT loss can thus accommodate temporal misalignment, leading to perceptually relevant optimization.

C2weakest assumption

That minimizing optimal transport cost between predicted and ground-truth note distributions produces perceptually superior transcriptions and that a harmonics-aware attention mechanism in the CRNN sufficiently captures the necessary spectro-temporal dependencies in piano signals.

C3one line summary

Introduces an optimal transport loss for neural piano transcription to accommodate temporal misalignments, achieving state-of-the-art onset detection on the MAESTRO dataset via a harmonics-aware CRNN.

References

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[1] INTRODUCTION In automatic piano transcription (APT) that aims to estimate a piano-roll representation (MIDI data) from a music record- ing [1], deep learning models play a central role. The standard p

[2] On- sets&Frames model [2] predicted note onsets and frame-wise activations separately and then combining them afterwards

[3] PROPOSED METHOD This section introduces the problem formulation of APT with OT and the proposed model architecture. 3.1. Problem formulation LetX∈R T×F be the time-frequency representation of a targe

[4] Each layer uses a7×7kernel and strides of (1,2), (1,2), and (2,1), progressively downsampling the tem- poral and frequency dimensions by factors of 2 and 4

[5] EV ALUA TION This section reports comparative evaluation conducted for val- idating the effectiveness of the OT loss in APT. 4.1. Experimental Conditions The MAESTRO [26] dataset was used for evaluati

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First computed	2026-05-20T00:03:56.794282Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

2b3693044f8e0653abb1be31215642fb7879cee28a835f87bda684bb54054b8d

Aliases

arxiv: 2605.17405 · arxiv_version: 2605.17405v1 · doi: 10.48550/arxiv.2605.17405 · pith_short_12: FM3JGBCPRYDF · pith_short_16: FM3JGBCPRYDFHK5R · pith_short_8: FM3JGBCP

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curl -sH 'Accept: application/ld+json' https://pith.science/pith/FM3JGBCPRYDFHK5RXYYSCVSC7N \
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Canonical record JSON

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    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.SD",
    "submitted_at": "2026-05-17T12:01:44Z",
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