Update README.md

README.md

@@ -25,13 +25,13 @@ size_categories:
 
 This dataset was created by scraping and segmenting over 4,000 episodes of the VOA Burmese morning radio program. From that archive, 3,687 MP3 files were extracted and processed. This dataset contains sentence-level audio chunks suitable for ASR and speech-related model training.
 
-The current release (`voa_batch_001.tar` and `voa_batch_002.tar`) contains a combined total of **~152,300 sentence-level audio chunks** derived from the first **420 MP3 files** in the archive, totaling approximately **420 hours** of segmented audio.
+The current release (`voa_batch_001.tar` and `voa_batch_003.tar`) contains a combined total of **~152,300 sentence-level audio chunks** derived from the first **420 MP3 files** in the archive, totaling approximately **420 hours** of segmented audio.
 
 - 🗂️ Contains ~152,300 sentence-level audio chunks
 - ⏱️ Total duration: ~420 hours (1.5 million seconds)
 - 🔊 Average chunk length: ~9.9 seconds
 - 🎵 Audio format: 16kHz mono MP3
-- 📦 2 WebDataset .tar files (`b1`, `b2`)
+- 📦 2 WebDataset .tar files 
 - 📏 Min chunk: 0.04 sec | Max chunk: 15.00 sec
   
 Each .mp3 is paired with a .json file containing structured metadata including file_name, broadcast_date, url, and duration.
@@ -40,13 +40,11 @@ Each .mp3 is paired with a .json file containing structured metadata including f
 
 ## Usage
 
-## Usage
-
 ```python
 from datasets import load_dataset
 
 # Stream all TARs under /train/
-ds = load_dataset("freococo/voa_myanmar_asr_audio", split="train", streaming=True)
+ds = load_dataset("freococo/voa_myanmar_asr_audio_2", split="train", streaming=True)
 
 sample = next(iter(ds))
 meta = sample["json"]
@@ -139,7 +137,7 @@ If you use this dataset, please cite it as:
   author       = {freococo},
   title        = {VOA Burmese – ASR-Ready WebDataset},
   year         = {2025},
-  url          = {https://huggingface.co/datasets/freococo/voa_myanmar_asr_audio},
+  url          = {https://huggingface.co/datasets/freococo/voa_myanmar_asr_audio_2},
   note         = {Segmented WebDataset format, public-domain VOA speech}
 }
 ```