README.md

---
license: other
license_name: mixed-creative-commons
pretty_name: Internet Archive Music Dataset (IAMD v0)
size_categories:
- 1M<n<10M
task_categories:
- audio-classification
- text-to-audio
- audio-text-to-text
tags:
- music
- music-captioning
- audio-captioning
- creative-commons
configs:
- config_name: default
  data_files:
  - split: train
    path: data/iamd-*.parquet
---

# Internet Archive Music Dataset (IAMD v0)

~4.2M thirty-second music segments (34,469 hours) sourced from
Creative-Commons audio on the [Internet Archive](https://archive.org), 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:

```python
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:

```python
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.