voice-note-to-midi

To convert a voice memo to MIDI, you can use a pipeline that applies stem separation and pitch detection to extract melodies, automatically outputting a clean, quantized MIDI file ready for editing in digital audio workstations.

Yes, you can transcribe humming into quantized MIDI automatically by using machine-learning pitch estimation combined with key detection, which processes the audio to produce accurate musical timing and note data.

Voice to MIDI conversion handles background noise by applying HPSS-based stem separation to isolate the melodic audio from unwanted sounds before running pitch detection and quantization.

Yes, you need Python 3.11 or higher to run the audio to MIDI conversion, along with the provided installation script to set up the environment and optional FFmpeg for processing audio files.

The best way to clean up pitch detection errors in generated MIDI is to use post-processing steps like octave pruning, harmonic removal, and legato merging, ensuring the extracted notes are accurate and musically coherent.

Extracted MIDI can have timing issues if key-aware quantization is not applied; utilizing automatic key detection and post-processing aligns the extracted pitch data to a clean musical grid.