diff --git a/README.md b/README.md index 7d13cc6f86c221a14e4f973d5f60ec275e3707a3..8132912542a62f2a60107c132996ed3dc053facc 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ --- -pretty_name: AudioSet (audio, 10 s clips, FLAC) +pretty_name: AudioSet license: other license_name: youtube-derived-audio license_link: https://research.google.com/audioset/download.html @@ -10,9 +10,12 @@ task_categories: tags: - audioset - audio -- sound-events -- noise -- speech-enhancement +- sound-event-detection +- audio-tagging +- 48khz +- flac +- webdataset +- deduplication size_categories: - 1M + AudioSet +

+ +# 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.** -The labelled 10 s window of every AudioSet segment, downloaded from YouTube between August and September 2026 and stored as -FLAC at the source sample rate, packed into tar shards of about 4 GB, with Google's original label files and a per-segment -metadata table that maps each clip to its shard. 1,605,881 of the 2,084,320 segments could be fetched (1.89 TiB); the rest -are listed with the reason they are missing. +| 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 | + +- **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, ...). +- **Originals kept.** The first 2026 download (44.1 kHz AAC for most clips) stays in the repository for codec comparisons. ## Contents -| path | what | -|---|---| -| `metadata/*_segments.csv`, `class_labels_indices.csv`, `ontology.json`, `qa_true_counts.csv` | Google's label files, unchanged | -| `metadata/clips.parquet` | one row per segment: `ytid`, `split`, `start_s`, `end_s`, `labels` (list of ontology ids), `available`, `bytes`, `reason`, `shard`, `member` | -| `subsets/noise_bank.parquet` | the segments with no speech and no music (by label), with a coarse category (room, outdoor, traffic, wind, water, crowd, machine, animal, other) | -| `audio//-NNNN.tar` | FLAC clips, members named `_.flac`, in `(split, ytid, start)` order | -| `preview/*.parquet` | 5,000 clips of the balanced split as Parquet with the audio embedded and the label names, for the dataset viewer (`audio`, `labels`, `label_names`, `shard`, `member`) | +- [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) -| split | segments | available | shards | -|---|---|---|---| -| eval | 20,371 | 15,460 | 5 | -| balanced_train | 22,160 | 16,324 | 5 | -| unbalanced_train | 2,041,789 | 1,574,097 | 474 | +## Quick start -Segments that could not be fetched, by reason: +Access is gated: accept the terms on this page, then log in with `huggingface-cli login`. -| reason | segments | -|---|---| -| video removed | 240,020 | -| private or login-gated | 116,362 | -| unplayable | 85,705 | -| fetch error | 18,962 | -| age-restricted | 6,602 | -| extractor error | 5,750 | -| private | 3,690 | -| download incomplete | 1,075 | -| NO_AUDIO_FORMAT | 272 | -| bot wall | 1 | +**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** -## Viewer +```python +import webdataset as wds +from huggingface_hub import get_token, hf_hub_url -The viewer shows the `preview` configuration: 5,000 clips of the balanced split with players and Google's label names, plus the -`shard` and `member` that locate the same clip in the full tar shards. The `metadata` configuration is the per-segment table for -all 2,084,320 segments and `noise_bank` the no-speech / no-music subset. The full audio lives in the tar shards below. +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 "_", audio under "flac" +``` -## Loading +**Listen in the viewer, or load the preview with `datasets`** ```python -from huggingface_hub import hf_hub_download, snapshot_download -import pyarrow.parquet as pq, tarfile, io, soundfile as sf - -meta = pq.read_table(hf_hub_download("Muno459/audioset", "metadata/clips.parquet", repo_type="dataset")).to_pandas() -row = meta[meta.available].iloc[0] -tar = hf_hub_download("Muno459/audioset", row.shard, repo_type="dataset") -with tarfile.open(tar) as tf: - audio, sr = sf.read(io.BytesIO(tf.extractfile(row.member).read())) +from datasets import load_dataset +preview = load_dataset("Muno459/AudioSet", "preview", split="balanced_train") # 5,000 clips with embedded audio and label names ``` -For streaming training, the shards are plain tar files with one FLAC per member, so `webdataset` can read them directly -(`wds.WebDataset(urls).decode(wds.torch_audio)`); `metadata/clips.parquet` carries the labels for every member. +## 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//-NNNN.tar` | **this release**: one FLAC per clip, members `_.flac`, about 4 GB per shard | +| `audio_v1//-NNNN.tar` | the first 2026 download as fetched, mostly 44.1 kHz AAC (see `aac_shard`, `aac_member`) | +| `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 | +| `aac_shard`, `aac_member` | the same clip as first downloaded (44.1 kHz AAC), where that differs from this release | +| `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 -## Provenance and quality +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: -Google releases AudioSet as CSV pointers to YouTube ids with 128-d embeddings; the audio itself has to be fetched per clip. -This copy was fetched with a resumable three-stage downloader (probe, extract, fetch) and each file was decoded once after -download to confirm it plays. The audio comes from YouTube's AAC stream (44.1 kHz stereo, low-passed around 16 kHz by the -encoder), not the Opus stream; if you need content above 16 kHz, `agkphysics/AudioSet` holds an Opus-sourced 48 kHz -release of the same segments. The channel layout is as served and the 10 s window follows the segment's `start_s`. -Nothing was resampled, normalised or re-encoded beyond the FLAC container. `qa_true_counts.csv` is Google's own label quality assessment. +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% | + +
+All reasons + +| 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 | + +
+ +## 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 released by Google under CC BY 4.0. The audio is YouTube content owned by its uploaders -and is not covered by that licence; it is shared here for non-commercial research under gated access, and requesters agree -not to redistribute it. If you are a rights holder and want a clip removed, open a discussion on this repository with the -YouTube id. +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 -Gemmeke, J. F., Ellis, D. P. W., Freedman, D., Jansen, A., Lawrence, W., Moore, R. C., Plakal, M., Ritter, M. (2017). -Audio Set: An ontology and human-labeled dataset for audio events. ICASSP 2017. +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. diff --git a/assets/banner.png b/assets/banner.png new file mode 100644 index 0000000000000000000000000000000000000000..2da17077a9e2c19c02b9ff592c833ba8a92a2cf2 --- /dev/null +++ b/assets/banner.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f40124f268210bada776608c64f8806424bff3019c6b719a306a61796095dd4d +size 855703 diff --git a/audio/balanced_train/balanced_train-0000.tar b/audio_v1/balanced_train/balanced_train-0000.tar similarity index 100% rename from audio/balanced_train/balanced_train-0000.tar rename to audio_v1/balanced_train/balanced_train-0000.tar diff --git a/audio/balanced_train/balanced_train-0001.tar b/audio_v1/balanced_train/balanced_train-0001.tar similarity index 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