README.md

metadata

license: cc-by-sa-4.0
pretty_name: Captioned MIDI with ChordStream
task_categories:
  - text-to-audio
tags:
  - midi
  - music
  - captions
  - chords
  - symbolic-music
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: i
      dtype: int64
    - name: source
      dtype:
        class_label:
          names:
            '0': godzilla
            '1': midicaps_prose
            '2': pdmx
    - name: caption
      dtype: string
    - name: key_tok
      dtype: string
    - name: midi_name
      dtype: string
    - name: midi
      dtype: binary
    - name: chordstream
      sequence: uint64
    - name: cs_tokens
      dtype: int32
    - name: cs_bars
      dtype: int32
    - name: cs_key
      dtype: string
    - name: cs_error
      dtype: string
  splits:
    - name: train
      num_bytes: 35220596
      num_examples: 900
    - name: test
      num_bytes: 3718590
      num_examples: 100
  download_size: 18872022
  dataset_size: 38939186

Captioned MIDI with ChordStream

1,000 captioned MIDI files, each with its harmony extracted as a ChordStream token sequence: one 64-bit token per chord change or silence, carrying the key, the chord's degree in that key, its pitch-class content, its bass, and its absolute bar, onset and length in musical time.

Rows are the first 1,000 midicaps_prose rows of PsiPi/captioned-midi-moods-and-genre (a private dataset), with the ChordStream column computed from each row's own midi bytes.

Splits

split	rows
train	900
test	100

Split 90/10 with train_test_split(test_size=0.1, seed=0).

Columns

column	meaning
i	row id in the source dataset
source	always midicaps_prose here
caption	the prose caption
key_tok	key as labelled in the source dataset
midi_name	{i}-{original file name}.mid
midi	the MIDI file's bytes
chordstream	the ChordStream tokens, uint64 per token
cs_tokens	number of tokens
cs_bars	bars covered
cs_key	key at the start of the piece, e.g. C, Am; the key can change, and each token carries its own
cs_error	empty, or why extraction produced nothing

Every token's top bit is zero, so the column is equally safe read as uint64 or int64. That is deliberate: numpy promotes uint64 above 2^63-1 to float64 whenever it meets a signed type, and Arrow refuses such values outright.

ChordStream token layout

A token is two 32-bit words: word_a = token & 0xFFFFFFFF, word_b = token >> 32.

Word A (chord)

bits	field	meaning
0-3	tonic	key tonic pitch class 0-11
4	mode	0 major, 1 minor
5-8	degree	chord root relative to the tonic 0-11; 14 = solo line, 15 = silence
9-19	mask	bit i-1 set means the interval i semitones above the root is present
20-23	bass	bass pitch class relative to the chord root
24-31	reserved	zero

Word B (time)

bits	field	meaning
0-15	bar	absolute bar from the start of the piece
16-21	onset	sixteenths after the bar's downbeat
22-29	dur	length in sixteenths (1-255)
30	cont	1 = continuation of the previous token (a chord that began earlier)
31	reserved	zero (the token's top bit)

The absolute chord root is (tonic + degree) mod 12. Everything except the tonic is relative to the key, so transposing a piece changes only the tonic. Time is in sixteenths derived from ticks, never from tempo, so playback speed cannot change a token. Every token carries its own bar, onset and key, so any contiguous slice is self-describing: a window whose first token has bar > 0 began mid-piece, and its cont flag says whether its chord started earlier.

Reading it

from datasets import load_dataset

PC = ["C", "Db", "D", "Eb", "E", "F", "Gb", "G", "Ab", "A", "Bb", "B"]
ROMAN = ["I", "bII", "II", "bIII", "III", "IV", "bV", "V", "bVI", "VI", "bVII", "VII"]

ds = load_dataset("PsiPi/captioned-ChordStream", split="train")
row = ds[0]

for tok in row["chordstream"]:
    a, b = tok & 0xFFFFFFFF, tok >> 32
    tonic, mode = a & 15, a >> 4 & 1
    degree, mask, bass = a >> 5 & 15, a >> 9 & 0x7FF, a >> 20 & 15
    bar, onset, dur, cont = b & 0xFFFF, b >> 16 & 63, b >> 22 & 255, b >> 30 & 1

    if degree == 15:
        name = "N.C."                      # silence
    elif degree == 14:
        name = "solo"                      # a single line, no harmony to name
    else:
        root = (tonic + degree) % 12
        minorish = mask >> 2 & 1 and not mask >> 3 & 1      # minor third, no major third
        numeral = ROMAN[degree].lower() if minorish else ROMAN[degree]
        intervals = [i for i in range(1, 12) if mask >> (i - 1) & 1]
        name = f"{numeral} {PC[root]} intervals={intervals} bass=+{bass}"
    print(f"bar {bar}.{onset} dur {dur}{' cont' if cont else ''} "
          f"key {PC[tonic]}{'m' if mode else ''}  {name}")

How the harmony was extracted

Per chord step (the metre's beat, grouped to at least a quarter note), a duration-weighted pitch-class histogram is matched against 16 chord templates, with melody voices downweighted, pedal points removed and refitted, unaccompanied single lines marked as solo, passing chords absorbed and consecutive same-root steps merged. The key comes from Aarden-Essen profiles over a sliding 8-bar window with hysteresis. The full procedure, with every threshold, is in the ChordStream write-up (see Citation and further reading).

Known limitations

• The extractor is heuristic and has not been validated against human harmonic annotation. Chord quality is the noisy part: power chords, add9 and sus2 are over-produced where melody notes leak into the chord. Roots and cadences are more reliable.
• Only major and minor keys are modelled.
• 3 of the 1,000 rows produced no tokens (cs_error is no pitched notes: the file has drums only or no notes the extractor uses). They are kept, with empty token lists, so rows stay aligned with the source dataset.
• Expressive performances (a recorded performance with a dense tempo map rather than a quantised score) have nominal bar lines, so chord steps placed on them may not match the harmonic rhythm a listener hears. This has not been measured.

Licence and provenance

The MIDI files come from the midicaps_prose portion of the parent dataset, which is MidiCaps over the Lakh MIDI dataset: CC BY-SA 4.0.

The captions are not MidiCaps captions. They were written for this project by PsiPi, generated with Anthropic models at PsiPi's own expense, and are licensed CC BY-SA 4.0.

The ChordStream column is derived from the MIDI files in the same rows.

Citation and further reading

The ChordStream format, its extraction procedure and its measured limitations are described in the accompanying write-up: https://huggingface.co/blog/PsiPi/chordstream-a-key-relative-time-anchored-chord-tok