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README.md
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pretty_name: AudioSet-Strong-10
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license: cc-by-4.0
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task_categories:
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- audio-classification
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tags:
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- sound-event-detection
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- audioset
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- strong-labels
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---
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# AudioSet-Strong-10
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paced to respect YouTube limits and the repository grows as clips arrive.
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## Classes
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Official strong labels contain 15,052 train / 2,217 eval unique clips for these
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classes (the paper's ten-class release is 15,829 / 2,394).
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## Contents
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```
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audio/train/<ytid>_<
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<
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```
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## Licence and credit
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- Audio
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## Citation
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---
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pretty_name: AudioSet-Strong-10
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license: cc-by-4.0
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task_categories:
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- audio-classification
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- audio-tagging
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tags:
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- sound-event-detection
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- audioset
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- strong-labels
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- temporal-annotations
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size_categories:
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- 10K<n<100K
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# AudioSet-Strong-10
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A ten-class, strong-label, 10-second-clip subset of **AudioSet-Strong**, with
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clip-relative event onsets and offsets. Built for streaming / bounded-latency
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sound event detection, where you need per-event times rather than clip tags.
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## Classes
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| Class | AudioSet MID |
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|---|---|
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| Alarm | `/m/07pp_mv` |
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| Bark | `/m/05tny_` |
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| Cough | `/m/01b_21` |
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| Explosion | `/m/014zdl` |
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| Gunshot | `/m/032s66` |
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| Laughter | `/m/01j3sz` |
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| Screaming | `/m/03qc9zr` |
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| Vehicle horn | `/m/0912c9` |
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| Whispering | `/m/02rtxlg` |
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| Whistling | `/m/01w250` |
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The official strong annotations contain **15,052 train** and **2,217 eval**
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unique 10-second clips for these ten classes.
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## Coverage in this release
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| Split | Official clips | In this release | Coverage |
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|---|---:|---:|---:|
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| train | 15,052 | 13,651 | 90.7% |
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| eval | 2,217 | 1,888 | 85.2% |
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| **total** | **17,269** | **15,539** | **90.0%** |
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35,183 clip-relative event rows in total. Every clip has at least one event.
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`missing.tsv` lists the 1,730 segment ids that could not be retrieved from
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YouTube or from the mirror (the underlying videos are deleted).
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Event rows per class (train / eval):
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| Class | train | eval |
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|---|---:|---:|
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| Alarm | 1,430 | 264 |
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| Bark | 5,706 | 465 |
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| Cough | 1,878 | 323 |
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| Explosion | 1,036 | 168 |
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| Gunshot | 3,114 | 321 |
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| Laughter | 10,702 | 1,682 |
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| Screaming | 1,215 | 246 |
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| Vehicle horn | 1,729 | 250 |
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| Whispering | 1,453 | 263 |
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| Whistling | 2,598 | 340 |
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## Contents
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```
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audio/train/<ytid>_<start_ms>.wav 16 kHz mono PCM16, 10 s
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audio/eval/<ytid>_<start_ms>.wav
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train_events.csv path,onset,offset,label
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eval_events.csv
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missing.tsv official clips that were unavailable
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```
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`<ytid>_<start_ms>` is the official AudioSet `segment_id`: the YouTube id and
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the start of the 10-second window in milliseconds. `onset`/`offset` are seconds
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**inside the clip** (0-10), so a row is directly usable as a strong label.
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One clip can have several rows (several labelled events). Every clip has at
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least one event from the ten classes above; other AudioSet classes that occur
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in the same window are not annotated here.
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## Provenance and completeness
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1. Segment ids, labels and event times come from the official
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`audioset_train_strong.tsv` / `audioset_eval_strong.tsv`
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(`storage.googleapis.com/us_audioset`), filtered to the ten MIDs.
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2. Audio is the 10-second window containing the labelled event, downloaded
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from YouTube with `yt-dlp` and resampled to 16 kHz mono.
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3. Clips whose YouTube video is deleted are recovered from the public
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`CLAPv2/audioset_strong` mirror (same official windows). Annotation times
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still come from the official TSVs; the mirror only supplies audio bytes.
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Harvested clips were cross-checked against the mirror's own event list
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(zero label mismatches).
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YouTube attrition is real: a share of the official videos is permanently
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unavailable. `missing.tsv` lists the segment ids that could not be obtained
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from either source at build time. Coverage is reported in the dataset card
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table below and should be re-checked before any comparison with published
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numbers on the complete strong set.
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## Licence and credit
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- Annotations: **CC BY 4.0**, Google AudioSet (Gemmeke et al., 2017).
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- Audio: downloaded from YouTube; rights remain with the original uploaders.
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This repository grants no rights over the audio and is released for research
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use, mirroring how AudioSet itself distributes the corpus. It may be removed
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on request.
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- The ten-class selection follows the AudioSet-Strong subset used by the
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RED+EPN line of work (Schmid et al.).
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## Citation
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```bibtex
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@misc{audioset_strong_10,
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title = {AudioSet-Strong-10: ten-class strong labels with 10-second audio},
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author = {LakoreAI},
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note = {Subset of AudioSet-Strong (Gemmeke et al., 2017)},
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year = {2026},
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url = {https://huggingface.co/datasets/LakoreAI/AudioSet-Strong-10}
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}
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```
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