# Smart Edition of MIDI Files

## TL;DR

This paper introduces Dancing MIDI, a model for editing non-quantized MIDI files that preserves musical nuances and relationships, addressing issues caused by naive editing methods.

## Contribution

The paper proposes a formal model with specific properties and operations for editing MIDI files, improving over naive methods by maintaining musical integrity.

## Key findings

- Dancing MIDI model prevents common editing problems.
- The model satisfies well-defined properties for editing operations.
- Effective in real-world applications like automatic harmonization.

## Abstract

We address the issue of editing musical performance data, in particular MIDI files representing human musical performances. Editing such sequences raises specific issues due to the ambiguous nature of musical objects. The first source of ambiguity is that musicians naturally produce many deviations from the metrical frame. These deviations may be intentional or subconscious, but they play an important role in conveying the groove or feeling of a performance. Relations between musical elements are also usually implicit, creating even more ambiguity. A note is in relation with the surrounding notes in many possible ways: it can be part of a melodic pattern, it can also play a harmonic role with the simultaneous notes, or be a pedal-tone. All these aspects play an essential role that should be preserved, as much as possible, when editing musical sequences. In this paper, we contribute specifically to the problem of editing non-quantized, metrical musical sequences represented as MIDI files. We first list of number of problems caused by the use of naive edition operations applied to performance data, using a motivating example. We then introduce a model, called Dancing MIDI, based on 1) two desirable, well-defined properties for edit operations and 2) two well-defined operations, Split and Concat, with an implementation. We show that our model formally satisfies the two properties, and that it prevents most of the problems that occur with naive edit operations on our motivating example, as well as on a real-world example using an automatic harmonizer.