Nathan Fradet- Sorbonne University
Nathan Fradet
- Sorbonne University
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6
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Introduction
Current institution
Publications
Publications (6)
We present and release MIDI-GPT, a generative system based on the Transformer architecture that is designed for computer-assisted music composition workflows. MIDI-GPT supports the infilling of musical material at the track and bar level, and can condition generation on attributes including: instrument type, musical style, note density, polyphony l...
We present and release MIDI-GPT, a generative system based on the Transformer architecture that is designed for computer-assisted music composition workflows. MIDI-GPT supports the infilling of musical material at the track and bar level, and can condition generation on attributes including: instrument type, musical style, note density, polyphony l...
The symbolic music modality is nowadays mostly represented as discrete and used with sequential models such as Transformers, for deep learning tasks. Recent research put efforts on the tokenization, i.e. the conversion of data into sequences of integers intelligible to such models. This can be achieved by many ways as music can be composed of simul...
This article presents MidiTok, a Python package to encode MIDI files into sequences of tokens to be used with sequential Deep Learning models like Transformers or Recurrent Neural Networks. It allows researchers and developers to encode datasets with various strategies built around the idea that they share common parameters. This key idea makes it...
