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How to Convert a Song to MIDI and Sheet Music

Getting a MIDI file or printable notation from a commercial recording used to mean transcribing by ear or paying someone to do it. AI transcription has made first drafts possible in seconds, but the quality varies enormously depending on what you give it. This guide covers what works, what does not, and how to get a usable result from audio-to-MIDI conversion and optical music recognition.

Last updated August 2026 · 9 min read

Two paths to MIDI and notation

JamScore AI offers two distinct transcription workflows, and choosing the right one depends on what you are starting with.

Audio-to-MIDI: from a recording to notation

If you have a song, an MP3, WAV, M4A, or OGG, and want MIDI or sheet music from it, you first separate the song into stems, then transcribe a specific stem. The transcription tool works on individual stems rather than a full mix, because asking an AI to disentangle the pitches of every instrument simultaneously from a stereo recording produces unreliable results. Separating first and transcribing second gives the model a much cleaner signal to work from.

Optical music recognition: from printed score to MIDI

If you already have a PDF or image of sheet music, a scanned orchestral part, a downloaded lead sheet, a photo of a textbook exercise, the optical music recognition (OMR) tool converts it directly to MIDI and MusicXML without needing an audio file at all. This is useful for digitising printed scores, generating playback from a static PDF, or getting an editable MIDI from a scan.

Step-by-step: audio to MIDI and sheet music

1. Upload your song and separate stems

   Go to JamScore AI and upload an MP3, WAV, M4A, or OGG file up to 10 minutes long. Click Separate. The AI splits the recording into six stems: vocals, drums, bass, guitar, piano, and other. If you are working with a song that has a clear instrumental part, a bass line, a piano riff, a vocal melody, this step will isolate it cleanly. If you are new to the separation process, the guide on isolating instrument stems covers what to expect from each stem type.

2. Identify the best stem for transcription

   This is the most important decision you will make. The AI transcription model works best on monophonic audio, one note at a time. A clean vocal stem, a bass line, a solo flute or violin, or a single-note keyboard melody will all transcribe well. A guitar chord stem, a piano pad, or the "other" stem (which often contains layers of synths and pads) will produce significantly more errors. See the caveat below before proceeding with dense or chordal material.

3. Select your notation format

   Click Transcribe on the stem you want. Choose your output format: staff notation (treble, bass, or grand staff), numbered notation (jianpu, widely used in Chinese music education), guitar TAB, bass TAB, or drum score. The app generates a MIDI file alongside the notation display regardless of which format you pick. If you want to edit the result further in a DAW or notation editor, the MIDI is the most portable starting point.

4. Run transcription and review the output

   The transcription runs in the browser and typically completes in 20??0 seconds depending on length and complexity. Once done, scan the notation carefully before assuming it is correct. Common issues to look for: notes placed an octave too high or too low; note lengths that do not match the original (particularly with sustained or slurred notes); missed ornaments such as grace notes or slides; and repeated notes rendered as a single long note. Make a mental list of corrections before exporting.

5. Export the MIDI or print the notation

   Download the MIDI file to use in a DAW (Ableton, Logic, GarageBand, Reaper) or notation software (MuseScore, Sibelius, Finale, Dorico). The notation view in the browser can be printed directly. If you want MusicXML for import into notation software, that export is also available alongside the MIDI.

Polyphonic material transcribes poorly, plan to correct by hand. If you are transcribing a piano chord voicing, strummed guitar, or any stem where multiple notes sound simultaneously, expect the output to need substantial correction. Common problems include octave errors on bass notes, merged notes where the AI interprets two closely voiced pitches as one, and rhythmic approximation errors on syncopated or swing passages. Think of the AI output as a first draft that gets you 60??0% of the way there on clean monophonic material, and perhaps 30??0% of the way there on chordal or dense polyphonic audio. Budget time for correction accordingly.

Step-by-step: optical music recognition (OMR)

If your starting point is printed sheet music rather than audio, the OMR workflow is separate from stem separation entirely.

1. Prepare your score file

   Scan or photograph your sheet music. PDF files work well if they are typeset (e.g. exported from notation software or downloaded from a legal score site). For scanned images, a clean black-and-white scan at 300 DPI or higher gives the best results. Poor lighting, slanted pages, or heavy annotation with handwritten markings will reduce accuracy.

2. Upload to the OMR tool

   In JamScore AI, go to the sheet music conversion section and upload your PDF or image. You can upload multi-page PDFs; the tool processes each page in sequence.

3. Review and export

   The OMR engine returns MIDI and MusicXML. As with audio transcription, review before use, OMR can misread accidentals, grace notes, and complex tuplets. Typeset scores from reputable publishers will generally transcribe cleanly; handwritten parts are significantly harder and may require more corrections.

What the notation formats are actually useful for

Staff notation

The standard Western notation system. Use this if you are working with a voice teacher, a classical or jazz instrument teacher, or any context where conventional music reading is expected. The grand staff option (treble + bass clef together) is appropriate for keyboard transcriptions, though polyphonic piano parts will still require correction as described above.

Numbered notation (jianpu)

A solfège-like system common in Chinese music education and folk music traditions. Numbers 1?? represent the degrees of the scale, with octave dots and duration marks. If you teach or study in a context where jianpu is the primary literacy system, this output lets you work with a familiar notation language directly from an audio source.

Guitar and bass TAB

Tablature shows string and fret positions rather than absolute pitches. The guitar TAB output is generated from the guitar stem; bass TAB from the bass stem. TAB is useful for learning a specific performance, where on the neck a part is played, but it does not capture pitch precisely in the same way staff notation does. If you want to understand the harmonic content of a guitar part (the chord names, the intervals), staff notation or the MIDI output is more informative. The guide on isolating instrument stems has more on what the guitar and bass stems contain and what to expect from separation quality on different genres.

Drum score

The drum score assigns each percussion element to a standard staff position, kick drum, snare, hi-hat, crash, and so on. This is useful for drummers learning a specific groove or fill, or for producers who want to understand a drum pattern in detail. Drum separation quality varies by genre: acoustic drum kits separate more cleanly than electronic drums with heavy processing or samples blended into the mix.

Using transcribed MIDI for vocal practice

One underused application of the transcription tool is generating a reference melody for vocal practice. Once you have transcribed the vocal stem to MIDI, you can import it into a notation editor, see the exact pitches you are aiming for, and identify which intervals are giving you trouble, an awkward tritone leap, a high note approached from below that keeps going flat. Knowing the interval name and seeing it on a stave is often more useful than listening repeatedly and hoping the ear adjusts.

You can then take that understanding back into the backing track workflow: the guide on practising singing with backing tracks explains how to build a practice session around the specific phrases you have now identified. Combining transcription-informed knowledge with loop-based repetition over the stems is a significantly more focused approach than either method alone.

Frequently asked questions