Dataset card, Google label files, per-clip metadata with the shard map, noise-bank subset

README.md

@@ -101,9 +101,10 @@ For streaming training, the shards are plain tar files with one FLAC per member,
 
 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 sample rate is whatever YouTube served for that video (mostly 44.1 or 48 kHz, some
-lower), 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.
+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.
 
 ## Licence and terms