Update README.md

README.md

@@ -34,9 +34,14 @@ Documents have an average span of 171 pages showing the fittedness for long cont
 
 Youtube-Commons is the current reference dataset for Youtube videos under creative commons allowing for full commercial reuse. The dataset was noticeably used to train Nvidia's SOTA text to speech model <a href="https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2">Parakeet</a>.
 
-While the public version of Youtube-Commons only includes metadata and transcripts and has not been updated since 2024, our internal asset includes audio attached to transcripts and metadata for 4.1 Million videos. About 40% of the corpus is Non-English, with more than 100,000 samples in Spanish, Hindi, French, Russian, Portuguese or Korean.
+While the public version of Youtube-Commons only includes metadata and transcripts and has not been updated since 2024, our internal asset includes audio attached to transcripts and metadata for 4,363,162 videos (1 million hours). About 40% of the corpus is Non-English, with more than 100,000 samples in Spanish, Hindi, French, Russian, Portuguese or Korean.
 
-We provide an initial samples of 5,000 audio samples with associated metadata in parquet.
+We provide an initial sample of 1,136 audio files from YouTube (394 hours) published from 2009 to 2026 in 93 languages and 168 audio files from VoxPopuli/Europarl (84 hours) published from 2009–2020.
+
+Samples use the same structure as the final dataset and are distributed as 12 fully shuffled parquet files with three components:
+* Metadata scraped from the Youtube official API with original url, channel information, date of publication.
+* New transcripts made with state of the art ASR model, *not* the Youtube transcript (frequently faulty). These allow for full text search of the entire corpus.
+* Audio included directly in the parquet file, as is now common expectation for multimodal model training.
 
 ## Non-US Patents