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Internet Archive Music Dataset (IAMD v0)
~4.2M thirty-second music segments (34,469 hours) sourced from Creative-Commons audio on the Internet Archive, each paired with machine-generated natural-language captions and the original item metadata.
| Segments | 4.2M |
| Audio | 34k hours |
| Segment length | 30 s nominal (mean 29.22 s) |
| Format | MP3, 320 kbps CBR, native channels + sample rate |
| Shards | 2,320 Parquet files |
| Download size | 4.53 TB |
Loading
A standard Parquet dataset with the audio embedded as an Audio feature — no
special loader, no sidecar, no join:
from datasets import load_dataset
ds = load_dataset("Telecom-Paris/iamd_v0", split="train", streaming=True)
sample = next(iter(ds))
sample["audio"] # {"array": np.ndarray, "sampling_rate": int} — decoded
sample["caption"] # caption + all metadata are columns on the same row
Audio decoding needs a backend — pip install soundfile (or torchcodec,
depending on your datasets version).
Structure
Each shard is a Parquet file; each row is one segment, with the audio embedded
as an Audio column ({bytes, path}) next to its caption and metadata columns:
data/iamd-00000.parquet
row: audio = {bytes: <mp3>, path: "iamd_00000261.mp3"}
key, segment_path, caption_tinymu, artist, license_type, license_url, ...
Repeated item-level fields (artist, license, …) are dictionary-compressed by
Parquet rather than duplicated per row. Keys are synthetic (iamd_<8 digits>)
because source basenames contain dots, spaces and non-ASCII characters and are
not unique across items; the original relative path is kept in the
segment_path column.
Metadata fields
Carried through from the Internet Archive item record. Coverage varies widely — most items supply little beyond title and license.
| Field | Coverage |
|---|---|
identifier |
100.0% |
tags |
100.0% |
license_type |
100.0% |
license_version |
100.0% |
license_url |
100.0% |
license_source |
100.0% |
collection |
100.0% |
mediatype |
100.0% |
uploader |
100.0% |
publicdate |
100.0% |
review_count |
100.0% |
mtg_top50_top5 |
100.0% |
mtg_top50_probs |
100.0% |
mtg_genre_top5 |
100.0% |
mtg_genre_probs |
100.0% |
mtg_instrument_top5 |
100.0% |
mtg_instrument_probs |
100.0% |
openmic_top5 |
100.0% |
openmic_probs |
100.0% |
mtg_mood_top5 |
100.0% |
mtg_mood_probs |
100.0% |
title |
100.0% |
description |
80.2% |
artist |
75.9% |
creator |
75.6% |
year_clean |
61.1% |
date |
61.1% |
year |
19.5% |
language |
9.6% |
notes |
7.1% |
avg_stars |
4.4% |
review_bodies |
4.4% |
review_titles |
4.4% |
album |
1.9% |
external_ids |
1.2% |
audio_type |
0.5% |
genre |
0.1% |
rights |
0.1% |
musicbrainz_ids |
0.1% |
composer |
0.1% |
recording_mode |
0.0% |
credits |
0.0% |
venue |
0.0% |
barcode |
0.0% |
label |
0.0% |
catalog_number |
0.0% |
equipment |
0.0% |
bitrate |
0.0% |
sample_rate |
0.0% |
bit_depth |
0.0% |
city |
0.0% |
bpm |
0.0% |
bpm_numeric |
0.0% |
location |
0.0% |
theme |
0.0% |
bandcamp_url |
0.0% |
track |
0.0% |
country |
0.0% |
channels |
0.0% |
instruments |
0.0% |
mood |
0.0% |
arranger |
0.0% |
style |
0.0% |
ensemble |
0.0% |
release_type |
0.0% |
is_live |
0.0% |
discogs_url |
0.0% |
spotify_url |
0.0% |
file_count |
0.0% |
Audio provenance
Segments were cut from source files in several formats and then re-encoded to 320 kbps CBR MP3 for this release:
| Source format | Segments | Share |
|---|---|---|
mp3 |
3.6M | 86.94% |
wav |
269k | 6.33% |
flac |
233k | 5.48% |
ogg |
38k | 0.89% |
aiff |
15k | 0.35% |
This is a lossy re-encode. 87% of the sources were already MP3 at a lower bitrate (~224 kbps on average), so those segments have been through two lossy generations — encoding them at 320 kbps makes the files larger without recovering any information. The 12% whose source was WAV/FLAC/AIFF are a single generation from lossless. If you need the highest-fidelity version, work from the source corpus rather than this release.
Licensing
Every item carries its own Creative Commons license, recorded per sample in the
license_type and license_url columns.
| License | Segments | Share |
|---|---|---|
| CC BY-NC-SA (attribution, non-commercial, share-alike) | 2.7M | 63.87% |
| CC BY (attribution) | 565k | 13.32% |
| CC BY-SA (attribution, share-alike) | 547k | 12.88% |
| CC BY-NC (attribution, non-commercial) | 407k | 9.59% |
| CC0 1.0 (public domain dedication) | 14k | 0.33% |
73% of segments are NonCommercial (NC). The dataset as a whole is therefore not usable for commercial purposes without filtering to the permissive subset:
ds = ds.filter(lambda s: "NC" not in (s["license_type"] or ""))
NoDerivatives (*-ND) items are excluded from this release, because re-encoding
produces a derivative work their license does not permit us to redistribute.
Attribution requirements (BY) apply to nearly all segments; use the artist,
title and identifier columns to credit sources.
Citation
If you use this dataset, please cite the Internet Archive as the source of the underlying recordings and credit the individual works per their licenses.
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