# PianoKontext: Expressive Performance Rendering from Deadpan Context

Source: [PianoKontext: Expressive Performance Rendering from Deadpan Context](<https://www.sota2.com/research/paper/6a2a4151d33dfb23e7839569>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-06-15T06:00:01.180Z

Authors: Dmitrii Gavrilev

Published: 2026-06-10T16:20:24.000Z

## Abstract

Expressive performance rendering (EPR) aims to generate realistic performances constrained on sequences of notes. However, flow matching audio editing models manipulate only synchronized music samples of the same duration, limiting their understanding of expressive timing. We introduce PianoKontext, a flow matching rendering model for classical piano music that generates variable-length performances in the latent space of a pretrained Music2Latent model. We synthesize MIDI scores into deadpan audio and employ Dynamic Time Warping (DTW) in the latent space to construct paired data for training. The aligned embeddings are concatenated in DiT blocks, allowing for a simple and effective learning of the dependencies between the score and performances. Audio samples are available at our demo page: https://realfolkcode.github.io/pianokontext\_demo/.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Expressive Performance Rendering on Piano (test)](<https://www.sota2.com/research/sota/expressive-performance-rendering-on-piano-test.md>): Expressive Performance Rendering; Piano (test); Pitch DTW: 0.888.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2606.12282>)

[PDF](<https://arxiv.org/pdf/2606.12282.pdf>)

[Implementation](<https://github.com/realfolkcode/pianokontext>)