Update README.md

README.md

@@ -225,56 +225,60 @@ configs:
     path: rvn-features/test-*
 license: cc-by-nc-4.0
 ---
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 # Dataset Card for RepeatSynth
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 Synthetic portion of the audio datasets referenced in *Class-Agnostic Audio Repetition Counting*.
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 Code: https://github.com/Hamozwa/audio-counting
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 ## Dataset Summary
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 RS, RSN, and RVN are synthetic datasets containing varying levels of background noise. Every sample is uniformly 10 seconds long and contains between 0 and 8 repetition events.
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 | Config | Description |
 |---|---|
 | `rs`  | RepeatSound — clean, no added background noise |
 | `rsn` | RepeatSoundNoisy — background noise added |
 | `rvn` | RepeatVeryNoisy — the noisiest condition |
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-Each config has `train`, `validation`, and `test` splits.
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+Each config has `train`, `validation`, and `test` splits. `rs-features`, `rsn-features`, and `rvn-features` hold precomputed spectrograms and self-similarity matrices for the same clips (see "Feature configs" below) — most users only need the main configs above.
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 ```python
 from datasets import load_dataset
 ds = load_dataset("Hamozwa/RepeatSynth", "rsn", split="train")
 ```
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 ## Dataset Structure
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-| Field | Type | Description |
-|---|---|---|
-| `audio` | `Audio` | The 10-second wav clip |
-| `id` | `string` | Original filename stem |
-| `original_source` | `string` | The FSD50K clip this sample's repeated event was built from |
-| `num_repetitions` | `int` | Ground-truth repetition count (0–8) |
-| `events` | `list[{start: float, end: float}]` | Onset/offset (seconds) of each repeated event within the clip |
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+| Field | Type | Description | Why it's here |
+|---|---|---|---|
+| `audio` | `Audio` | The 10-second wav clip | The actual training/test input |
+| `id` | `string` | Original filename stem | Lets you cross-reference against the `-features` configs or reconstruct the original file layout |
+| `original_source` | `string` | The FSD50K clip this sample's repeated event was built from | Required for attribution — FSD50K licenses each clip individually, so this is what you check to find the license of the audio actually used in a given sample |
+| `num_repetitions` | `int` | Ground-truth repetition count (0–8) | The label WavCounter and TSSMCounter are trained/evaluated against |
+| `events` | `list[{start: float, end: float}]` | Onset/offset (seconds) of each repeated event within the clip | Used to build the target heatmap WavCounter regresses against, rather than just a single count — this is what lets the model localize events in time, not just count them |
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+## Feature configs
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+`rs-features`/`rsn-features`/`rvn-features` contain `id`, `spectrogram`, and `tssm` (temporal self-similarity matrix) columns: the precomputed inputs TSSMCounter and spectrogram baseline actually train on, joinable back to the main config via `id`. These are included for convenience and exact reproducibility, but are fully derivable from the `audio` column above via the preprocessing code in the linked repo, so they're kept as separate configs rather than bundled into the main table.
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 ## Dataset Sources
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 Synthetic clips were generated by combining two source collections:
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 - FSD50K — https://zenodo.org/records/4060432 — provided the audio for each repeated event
 - MUSAN — http://openslr.org/ — used as background noise
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 ## Licensing
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 This is a derivative work built from two source collections, each with different terms. Both require attribution.
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 **FSD50K** licenses each clip individually rather than as a whole collection (CC0, CC-BY, CC-BY-NC, or CC Sampling+, depending on the clip). Since every sample here is built from one specific FSD50K clip, the `original_source` field lets you look up that clip's exact license via FSD50K's own `dev_clips_info_FSD50K.json` / `eval_clips_info_FSD50K.json` mapping files. If you plan to use or redistribute a subset commercially, check the license of every clip referenced by `original_source` first — some are CC-BY-NC and restrict commercial reuse.
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 **MUSAN** is released under CC BY 4.0 (https://openslr.org/17/) — attribution required, otherwise unrestricted.
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 ## Citation
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 ```bibtex
 [Your paper's BibTeX entry here]
 ```