Update README.md

README.md

@@ -54,7 +54,7 @@ pretty_name: Quranic Audio Dataset - Crowdsourced and Labeled Recitation from No
 
 # Dataset Card for Quranic Audio Dataset : Crowdsourced and Labeled Recitation from Non-Arabic Speakers
 
-### Dataset Summary
+## Dataset Summary
 
 We explore the possibility of crowdsourcing a carefully annotated Quranic dataset, on top of which AI models can be built to simplify the learning process.
 In particular, we use the volunteer-based crowdsourcing genre and implement a crowdsourcing API to gather audio assets.
@@ -63,17 +63,71 @@ As a result, we have collected around 7000 Quranic recitations from a pool of 12
 We have achieved a crowd accuracy of 0.77, an inter-rater agreement of 0.63 between the annotators, and 0.89 between the labels assigned by the algorithm and the expert judgments.
 
 ## How to use
+The dataset can be downloaded using the `load_dataset` function from `datasets` library.
+
+```python
+!pip install datasets
+```
+
+```python
+from datasets import load_dataset
+
+quranic_dataset = load_dataset("RetaSy/quranic_audio_dataset")
+
+print(quranic_dataset)
+```
 
 ## Dataset Structure
 
 ### Data Instances
+```python
+{
+  'audio': {
+      'path': '0058a4f7-6a3a-4665-b43b-d6f67fd14dbf.wav',
+      'array': array([0.00000000e+00, 0.00000000e+00, 3.05175781e-05, ...,9.15527344e-05, 0.00000000e+00, 1.83105469e-04]),
+      'sampling_rate': 16000
+  },
+  'Surah': 'Al-Faatihah',
+  'Aya': 'أَعُوذُ بِاللَّهِ مِنَ الشَّيْطَانِ الرَّجِيْمِ',
+  'duration_ms': 3520,
+  'create_date': '2023-03-15T19:57:35.027430+03:00',
+  'golden': False,
+  'final_label': 'in_correct',
+  'reciter_id': 'ef1ada15-e225-4155-a81c-fc461d940a6d',
+  'reciter_country': 'AT',
+  'reciter_gender': 'female',
+  'reciter_age': 'Unknown',
+  'reciter_qiraah': 'hafs',
+  'judgments_num': 3,
+  'annotation_metadata': '{
+          "label_1": "in_correct",
+          "annotator1_id": "1",
+          "annotator1_SCT": "257",
+          "annotator1_MCC": "0.87",
+          "annotator1_ACC": "0.92",
+          "annotator1_F1": "0.91",
+          "label_2": "correct",
+          "annotator2_id": "10",
+          "annotator2_SCT": "21",
+          "annotator2_MCC": "0.52",
+          "annotator2_ACC": "0.57",
+          "annotator2_F1": "0.55",
+          "label_3": "in_correct",
+          "annotator3_id": "19",
+          "annotator3_SCT": "12",
+          "annotator3_MCC": "0.75",
+          "annotator3_ACC": "0.83",
+          "annotator3_F1": "0.78"
+  }'
+}
+```
 
 ### Data Fields
 
 ### Citation Information
 
 ```
-@inproceedings{commonvoice:2020,
+@inproceedings{quran_audio_dataset:2024,
   author      = {Salameh, R., Mdfaa, M. A., Askarbekuly, N., & Mazzara, M.},
   title       = {Quranic Audio Dataset: Crowdsourced and Labeled Recitation from Non-Arabic Speakers},
   year        = 2024,
@@ -81,8 +135,6 @@ We have achieved a crowd accuracy of 0.77, an inter-rater agreement of 0.63 betw
   eprinttype  = {arxiv},
   eprintclass = {cs.SD},
   url         = {https://arxiv.org/abs/2405.02675},
-  language    = {english},
-  booktitle   = {},
-  pages       = {}
+  language    = {english}
 }
 ```