AudioSet v2: 48 kHz audio, per-clip provenance, measurements, duplicate flags and missing-segment reasons; first download kept under audio_v1/

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<n<10M
 configs:
@@ -25,95 +28,341 @@ configs:
   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: "This dataset holds the 10 s AudioSet segments as downloaded from YouTube. Google publishes only the labels; the audio is YouTube content and stays under its terms. Access is granted for research use. By requesting access you confirm that you will use the audio for non-commercial research, will not redistribute it, and will comply with the YouTube Terms of Service and with any rights the content owners hold."
+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
 ---
 
-# AudioSet audio
+<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.**
 
-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/<split>/<split>-NNNN.tar` | FLAC clips, members named `<ytid>_<start_ms>.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 "<ytid>_<start_ms>", 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/<split>/<split>-NNNN.tar` | **this release**: one FLAC per clip, members `<ytid>_<start_ms>.flac`, about 4 GB per shard |
+| `audio_v1/<split>/<split>-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% |
+
+<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 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.