Update README.md

README.md

@@ -2,9 +2,7 @@
 dataset_info:
   features:
   - name: audio
-    dtype:
-      audio:
-        sampling_rate: 16000
+    dtype: audio
   - name: timestamps_start
     sequence: float64
   - name: timestamps_end
@@ -13,13 +11,13 @@ dataset_info:
     sequence: string
   splits:
   - name: dev
-    num_bytes: 2338411143.0
+    num_bytes: 2338411143
     num_examples: 216
   - name: test
-    num_bytes: 5015872396.0
+    num_bytes: 5015872396
     num_examples: 232
-  download_size: 7296385333
-  dataset_size: 7354283539.0
+  download_size: 7296384603
+  dataset_size: 7354283539
 configs:
 - config_name: default
   data_files:
@@ -27,4 +25,73 @@ configs:
     path: data/dev-*
   - split: test
     path: data/test-*
+tags:
+- speaker diarization
+- voice activity detection
+license: cc-by-4.0
+language:
+- en
 ---
+
+
+# Dataset Card for the Voxconverse dataset 
+
+VoxConverse is an audio-visual diarisation dataset consisting of multispeaker clips of human speech, extracted from YouTube videos. Updates and additional information about the dataset can be found on the [dataset website](https://www.robots.ox.ac.uk/~vgg/data/voxconverse/index.html).
+
+Note: This dataset has been preprocessed using [diarizers](https://github.com/huggingface/diarizers/tree/main/datasets). It makes the dataset compatible with diarizers to fine-tune [pyannote](https://huggingface.co/pyannote/segmentation-3.0) segmentation models.
+
+
+# Example Usage
+
+```
+from datasets import load_dataset
+ds = load_dataset("diarizers-community/voxconverse")
+
+print(ds)
+```
+
+gives: 
+
+```
+DatasetDict({
+    train: Dataset({
+        features: ['audio', 'timestamps_start', 'timestamps_end', 'speakers'],
+        num_rows: 136
+    })
+    validation: Dataset({
+        features: ['audio', 'timestamps_start', 'timestamps_end', 'speakers'],
+        num_rows: 18
+    })
+    test: Dataset({
+        features: ['audio', 'timestamps_start', 'timestamps_end', 'speakers'],
+        num_rows: 16
+    })
+})
+```
+
+# Dataset source
+
+- Homepage: https://www.robots.ox.ac.uk/~vgg/data/voxconverse/
+- Repository: https://github.com/joonson/voxconverse?tab=readme-ov-file
+- Preprocessed using [diarizers](https://github.com/kamilakesbi/diarizers/tree/main/datasets)
+
+
+# Citation
+
+```
+@article{chung2020spot,
+  title={Spot the conversation: speaker diarisation in the wild},
+  author={Chung, Joon Son and Huh, Jaesung and Nagrani, Arsha and Afouras, Triantafyllos and Zisserman, Andrew},
+  booktitle={Interspeech},
+  year={2020}
+}
+```
+
+# Contribution 
+
+Thanks to [@kamilakesbi](https://huggingface.co/kamilakesbi) and [@sanchit-gandhi](https://huggingface.co/sanchit-gandhi) for adding this dataset.
+
+
+
+
+