README.md

---

pretty_name: AudioSet
license: other
license_name: youtube-derived-audio
license_link: https://research.google.com/audioset/download.html
language:
- en
task_categories:
- audio-classification
tags:
- audioset
- audio
- sound-event-detection
- audio-tagging
- 48khz
- flac
- webdataset
- deduplication
size_categories:
- 1M<n<10M
configs:
- config_name: preview
  default: true
  data_files:
  - split: balanced_train
    path: preview/*.parquet
- config_name: metadata
  data_files:
  - split: all
    path: metadata/clips.parquet
- config_name: duplicates
  data_files:
  - split: all
    path: metadata/duplicates.parquet
- config_name: noise_bank
  data_files:
  - split: all
    path: subsets/noise_bank.parquet
gated: manual
extra_gated_prompt: "AudioSet's audio is YouTube content: Google publishes only the labels. Access is granted for non-commercial research. By requesting access you confirm that you will use the audio for non-commercial research only, will not redistribute it, and will respect the YouTube Terms of Service and the rights of the content owners."
extra_gated_fields:
  Affiliation: text
  Intended use: text
  I will use the audio for non-commercial research only and will not redistribute it: checkbox
---


<p align="center">
  <img src="assets/banner.png" alt="AudioSet" width="100%">
</p>

# AudioSet

**Google's AudioSet with the audio: 1,780,876 of its 2,084,320 labelled 10 s YouTube segments as 48 kHz FLAC, each with a

record of where its audio came from, measured quality, duplicate and eval-overlap flags, and a reason for every segment

that could not be found.**

| clips with audio | hours | classes | format | size |
|:---:|:---:|:---:|:---:|:---:|
| **1,780,876** of 2,084,320 (85.4%) | **4,904** | **527** | 48 kHz, 24-bit FLAC | 2.25 TiB |

The 48 kHz release in `audio48k/` is the only audio in this repository. The first download's 44.1 kHz AAC copy
(`audio_v1/`) was removed on 2026-09-30; where a clip exists only as AAC on YouTube, its audio here is that AAC stream
resampled to 48 kHz and flagged `native_48k = false`.

## Highlights

- **48 kHz throughout.** 87.9% of the clips are decoded from Opus streams (full band to 20 kHz). The rest
  exist only as AAC on YouTube; they are resampled to 48 kHz and flagged, never passed off as native.
- **Provenance on every clip.** Where the audio came from, which codec it was decoded from, and whether it was resampled.
- **Measured.** Bandwidth, energy above 16 kHz, peak and RMS level, clipping and silence for every clip.
- **Deduplicated.** Audio fingerprinting finds re-uploads and flags train clips whose audio also appears in the eval set.
- **Accounted for.** Each of the 303,444 missing segments carries one specific reason (removed, private, blocked, ...).

## Contents

- [Quick start](#quick-start)
- [How it compares](#how-it-compares)
- [Dataset structure](#dataset-structure)
- [How the audio was built](#how-the-audio-was-built)
- [Quality measurements](#quality-measurements)
- [Duplicates and eval overlap](#duplicates-and-eval-overlap)
- [Missing segments](#missing-segments)
- [Limitations](#limitations)
- [Licence and terms](#licence-and-terms)
- [Citation](#citation)

## Quick start

Access is gated: accept the terms on this page, then log in with `huggingface-cli login`.

**Browse and filter the metadata**

```python

import pandas as pd

from huggingface_hub import hf_hub_download



clips = pd.read_parquet(hf_hub_download("Muno459/AudioSet", "metadata/clips.parquet", repo_type="dataset"))

audio = clips[clips.available]



# a clean training pool: no overlap with eval, native 48 kHz only, one clip per group of identical audio

train = audio[(audio.split != "eval") & ~audio.eval_overlap & audio.native_48k]

train = train[train.dup_group.isna() | ~train.duplicated("dup_group")]

```

**Read a clip**

```python

import io, tarfile, soundfile as sf



row = train.iloc[0]

with tarfile.open(hf_hub_download("Muno459/AudioSet", row.shard, repo_type="dataset")) as tar:

    wav, sr = sf.read(io.BytesIO(tar.extractfile(row.member).read()))   # sr == 48000

```

**Stream the shards with WebDataset**

```python

import webdataset as wds

from huggingface_hub import get_token, hf_hub_url



auth = f"-H 'Authorization:Bearer {get_token()}'"

urls = [f"pipe:curl -s -L {auth} {hf_hub_url('Muno459/AudioSet', shard, repo_type='dataset')}" for shard in audio.shard.unique()]

dataset = wds.WebDataset(urls, shardshuffle=True).decode(wds.torch_audio)   # key "<ytid>_<start_ms>", audio under "flac"

```

**Listen in the viewer, or load the preview with `datasets`**

```python

from datasets import load_dataset

preview = load_dataset("Muno459/AudioSet", "preview", split="balanced_train")   # 5,000 clips with embedded audio and label names

```

## How it compares

[agkphysics/AudioSet](https://huggingface.co/datasets/agkphysics/AudioSet) is the most complete earlier release, and this
one builds on it (it is the source of 1,284,135 of the clips here).

| | this dataset | agkphysics/AudioSet |
|---|---|---|
| segments with audio | **1,780,876** | 1,774,481 |
| sample rate | 48 kHz for every clip | as downloaded; 44.1 kHz AAC for at least 214,890 clips |
| source and codec per clip | recorded (`source`, `source_codec`, `native_48k`) | not recorded |
| AAC-only clips | resampled and flagged (216,123) | mixed in, not distinguished |
| quality measurements | bandwidth, level, clipping, silence | none |
| digitally silent clips | removed | 1,185 (replaced here from YouTube where possible) |
| missing segments | one specific reason each | not listed |
| duplicates and eval overlap | 2,609 train clips overlap eval, flagged | not flagged |

## Dataset structure

### Files

| path | contents |
|---|---|
| `audio48k/<split>/<split>-NNNN.tar` | **this release**: one FLAC per clip, members `<ytid>_<start_ms>.flac`, about 4 GB per shard |
| `metadata/clips.parquet` | one row per AudioSet segment, all 2,084,320 |
| `metadata/duplicates.parquet` | every verified pair of clips with the same or partly the same audio |
| `metadata/*_segments.csv`, `class_labels_indices.csv`, `ontology.json`, `qa_true_counts.csv` | Google's release files, unchanged |
| `subsets/noise_bank.parquet` | clips labelled with neither speech nor music, with a coarse category; a clip can carry several |
| `preview/*.parquet` | 5,000 balanced-split clips with embedded audio, label names and provenance, for the viewer |

### Splits

| split | segments | with audio | share | shards |
|---|---:|---:|---:|---:|
| `balanced_train` | 22,160 | 18,765 | 84.7% | 7 |
| `unbalanced_train` | 2,041,789 | 1,744,882 | 85.5% | 566 |
| `eval` | 20,371 | 17,229 | 84.6% | 6 |

### `metadata/clips.parquet`

| column | description |
|---|---|
| `ytid`, `split`, `start_s`, `end_s` | the AudioSet segment |
| `labels` | ontology ids (`/m/...`), names in `class_labels_indices.csv` |
| `available` | the clip has audio in this release |
| `shard`, `member`, `bytes` | tar shard, member name and FLAC size |
| `source` | `youtube_2026` (fetched from YouTube, August to September 2026) or `agkphysics_2023` (from agkphysics/AudioSet) |
| `source_codec` | `opus` or `aac`: the stream the audio was decoded from |
| `native_48k` | `false` if resampled from 44.1 kHz AAC (no content above the AAC encoder's cutoff, typically about 16 kHz) |
| `sample_rate`, `channels`, `duration_s` | as stored; sample rate is always 48000 |
| `peak_dbfs`, `rms_dbfs` | sample peak and RMS level over all channels |
| `clipped_fraction` | share of samples at or above 0.999 of full scale |
| `silent_fraction` | share of 50 ms frames of the mono mix below -60 dBFS |
| `bandwidth_hz` | highest frequency whose smoothed level is within 50 dB of the 90th percentile level between 200 Hz and 4 kHz |
| `hf16_energy_db` | energy above 16 kHz relative to the total, in dB |
| `dup_group`, `dup_group_size` | near-identical clips (the same audio at the same position, within 1 s) share a group id |
| `same_audio_in`, `partial_audio_in` | splits of the clips this clip matches over the whole overlap, or over at least 3 s of it |
| `eval_overlap` | a train clip that matches an eval clip, or an eval clip that matches a train clip |
| `reason`, `reason_group`, `reason_checked` | for missing segments: why, the group it counts under, and the date it was last checked |

## How the audio was built

Google publishes AudioSet as YouTube ids with time stamps; the audio has to be fetched per segment. It was fetched in
August and September 2026 and then rebuilt clip by clip, preferring Opus (48 kHz, full band to 20 kHz) over AAC (44.1 kHz,
typically low-passed near 16 kHz), since a paired comparison on the same segments found the Opus stream never measurably worse:

1. **Opus copy from agkphysics/AudioSet**, accepted only if it is the same recording as the 2026 download (normalised
   cross-correlation of at least 0.5 after alignment), not silent, not shorter, and not narrower below 20 kHz.
2. **Opus stream from YouTube**, fetched again under the same checks when agkphysics had no usable copy. Noisy recordings
   lose waveform shape through two different codecs, so a correlation between 0.3 and 0.5 is also accepted when the
   audio fingerprints match (bit error rate at most 0.20 at the aligned offset).
3. **Resampled AAC**, only when no Opus version exists (older uploads often have none) or the Opus copy failed the checks:
   polyphase resampling from 44.1 to 48 kHz (Kaiser window, beta 10), flagged `native_48k = false`.

Segments YouTube no longer serves were filled from agkphysics/AudioSet under the same checks. Every file was decoded
back, its sample rate and duration verified, and rejected if its peak was at or below -70 dBFS. Nothing is normalised,
and the channel layout is as served.

| audio | `source` | `source_codec` | `native_48k` | clips | share |
|---|---|---|---|---:|---:|
| Opus copy from agkphysics/AudioSet (2023) | `agkphysics_2023` | `opus` | `true` | 1,268,580 | 71.2% |
| Opus stream from YouTube (2026) | `youtube_2026` | `opus` | `true` | 296,173 | 16.6% |
| AAC stream from YouTube (2026), resampled | `youtube_2026` | `aac` | `false` | 200,568 | 11.3% |
| AAC copy from agkphysics/AudioSet (2023), resampled | `agkphysics_2023` | `aac` | `false` | 15,555 | 0.9% |

## Quality measurements

Every clip was measured from the final file (definitions in the column table above).

| | value |
|---|---|
| clips with content up to at least 19 kHz | 26.0% |
| median `bandwidth_hz`, native 48 kHz clips | 15,574 Hz |
| median `bandwidth_hz`, resampled AAC clips | 14,484 Hz |
| clips with more than 0.1% clipped samples | 116,646 |

Many recordings are narrower than their codec allows (phone and camera microphones, old uploads); `bandwidth_hz` shows
this directly, so band-limited audio can be filtered out or used on purpose.

## Duplicates and eval overlap

Every clip was fingerprinted (32-bit sub-fingerprints from band-energy differences of the 8 kHz mono mix, 32 ms hop,
after Haitsma and Kalker) and looked up against every other clip at any time offset. A pair is **the same audio** when
the bit error rate over the whole overlap (at least 3 s of active audio) is at most 0.25, and **partly shared** when some
3 s stretch matches at 0.12 or less; unrelated audio sits near 0.5. In an audit of 100 random accepted pairs across the
full dataset, 75 were confirmed as the same recording by local waveform correlation (19 of 20 below a bit error rate of
0.05); most of the rest are the same music with tempo, mix or phase differences that waveform correlation cannot follow.
Treat matches near the 0.25 limit as likely rather than certain: `metadata/duplicates.parquet` carries the error rate.

| | clips |
|---|---|
| clips in a group of near-identical clips | 53,772 in 19,425 groups |
| extra copies (dropped by keeping one per group) | 34,347 |
| train clips with the same audio as an eval clip | 2,425 |
| train clips sharing at least 3 s with an eval clip (`eval_overlap`) | 2,609 |
| eval clips sharing at least 3 s with a train clip (`eval_overlap`) | 922 |

The overlaps come from YouTube itself: one video uploaded under several ids, compilations that reuse clips, popular music
reused across many videos, and channel intros, each labelled by AudioSet as an independent segment.

Groups (`dup_group`) hold near-identical clips: every member matches the group's representative clip directly (bit error
rate at most 0.20, offset within 1 s, at least 8 s of overlap), so songs reused at different offsets across many videos
cannot chain unrelated clips into one group. `same_audio_in`, `partial_audio_in` and `eval_overlap` use every verified pair.
`metadata/duplicates.parquet` lists every pair with its bit error rate, offset and overlap.

## Missing segments

303,415 of the 303,444 missing segments were retried from YouTube between 2026-09-14 and 2026-09-15; each missing segment carries the single most specific reason YouTube gave.

| reason group | segments | share of AudioSet |
|---|---:|---:|
| removed | 206,398 | 9.9% |
| private or restricted | 88,600 | 4.3% |
| blocked by region or claim | 6,457 | 0.3% |
| stream refused | 1,024 | <0.1% |
| no usable audio | 936 | <0.1% |
| other | 29 | <0.1% |

<details>
<summary>All reasons</summary>

| group | reason | segments |
|---|---|---:|
| removed | video unavailable, no reason given (removed) | 136,969 |
| removed | uploader account terminated | 53,338 |
| removed | removed for a Terms of Service violation | 6,676 |
| removed | removed after a copyright claim | 4,997 |
| removed | removed for a Community Guidelines violation | 2,794 |
| removed | removed under YouTube's policy on violent or graphic content | 853 |
| removed | removed under YouTube's policy on nudity or sexual content | 274 |
| removed | removed under YouTube's policy on harassment and bullying | 163 |
| removed | removed by the uploader | 153 |
| removed | removed under YouTube's policy on spam, deceptive practices, and scams | 66 |
| removed | removed after a privacy claim | 65 |
| removed | removed as a duplicate of another video | 40 |
| removed | removed after a trademark claim | 10 |
| private or restricted | private video | 87,794 |
| private or restricted | video not available, no reason given | 561 |
| private or restricted | age-restricted, sign-in required | 134 |
| private or restricted | sign-in required | 70 |
| private or restricted | channel members only | 41 |
| blocked by region or claim | blocked by a content claim | 5,415 |
| blocked by region or claim | rights holder blocked the fetch region | 788 |
| blocked by region or claim | not available in the fetch region | 175 |
| blocked by region or claim | uploader blocked the fetch region | 79 |
| stream refused | audio stream refused by the CDN (HTTP 403) | 530 |
| stream refused | stream served only up to its first MiB, segment lies past it | 486 |
| stream refused | temporarily unavailable when fetched | 7 |
| stream refused | audio fetch failed | 1 |
| no usable audio | audio track is digital silence | 572 |
| no usable audio | the labelled 10 s window is digital silence | 240 |
| no usable audio | segment starts after the end of the video | 124 |
| other | unplayable, no reason given | 20 |
| other | YouTube error, no reason given | 9 |

</details>

## Limitations

- **Labels are Google's.** They are clip-level and weakly verified; `qa_true_counts.csv` is Google's own estimate of label
  quality per class.
- **Resampled clips are not full band.** The 216,123 clips with `native_48k = false` are 48 kHz files carrying
  AAC audio, with nothing above the AAC cutoff. Filter on `native_48k` when that matters.
- **The audio is today's YouTube audio**, checked against our own 2026 download, not against what Google's raters heard in
  2017. Uploaders can re-edit videos; a small number of segments may no longer match their labels.
- **Duplicate detection is a threshold.** An audit confirmed 75 of 100 random matches as the same recording by waveform
  correlation, with the rest mostly music the check cannot follow; the pair table carries the bit error rate so stricter
  cut-offs are one filter away. Eval-overlap flags err on the side of excluding a clip.

## Licence and terms

The labels and the ontology are © Google, released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). The
audio is YouTube content owned by its uploaders and is not covered by that licence. It is shared for non-commercial
research under gated access, and requesters agree not to redistribute it. Rights holders who want a clip removed can open
a discussion on this repository with the YouTube id.

## Citation

If you use this dataset, please cite AudioSet:

```bibtex

@inproceedings{gemmeke2017audioset,

  title     = {Audio Set: An ontology and human-labeled dataset for audio events},

  author    = {Gemmeke, Jort F. and Ellis, Daniel P. W. and Freedman, Dylan and Jansen, Aren and

               Lawrence, Wade and Moore, R. Channing and Plakal, Manoj and Ritter, Marvin},

  booktitle = {2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},

  pages     = {776--780},

  year      = {2017},

  doi       = {10.1109/ICASSP.2017.7952261}

}

```

and this release:

```bibtex

@misc{audioset48k2026,

  title        = {AudioSet at 48 kHz: audio, provenance, quality measurements and duplicate flags for the AudioSet segments},

  author       = {Muno459},

  year         = {2026},

  howpublished = {Hugging Face},

  url          = {https://huggingface.co/datasets/Muno459/AudioSet}

}

```

The duplicate search follows:

```bibtex

@inproceedings{haitsma2002robust,

  title     = {A Highly Robust Audio Fingerprinting System},

  author    = {Haitsma, Jaap and Kalker, Ton},

  booktitle = {Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR)},

  year      = {2002}

}

```

## Acknowledgements

AudioSet was created by the Sound Understanding group at Google Research ([research.google.com/audioset](https://research.google.com/audioset/)).
Clips with `source = agkphysics_2023` come from [agkphysics/AudioSet](https://huggingface.co/datasets/agkphysics/AudioSet),
without which many segments whose videos have since disappeared would be lost.