Update README.md

README.md

@@ -13,7 +13,31 @@ dataset_info:
     num_examples: 39238
   download_size: 10866820110
   dataset_size: 10917088956.322
+task_categories:
+- automatic-speech-recognition
+language:
+- pa
+tags:
+- punjabi
+- asr
+- transcription
+- translation
+pretty_name: Punjabi ASR
+size_categories:
+- 10K<n<100K
 ---
-# Dataset Card for "punjabi-asr"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+# Dataset for Punjabi ASR
+Shrutilipi is a labelled ASR corpus obtained by mining parallel audio and text pairs at the document scale from All India Radio news bulletins for 12 Indian languages: Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Punjabi, Sanskrit, Tamil, Telugu, Urdu. The corpus has over 6400 hours of data across all languages.
+
+```
+@misc{https://doi.org/10.48550/arxiv.2208.12666,
+  doi = {10.48550/ARXIV.2208.12666},
+  url = {https://arxiv.org/abs/2208.12666},
+  author = {Bhogale, Kaushal Santosh and Raman, Abhigyan and Javed, Tahir and Doddapaneni, Sumanth and Kunchukuttan, Anoop and Kumar, Pratyush and Khapra, Mitesh M.},
+  title = {Effectiveness of Mining Audio and Text Pairs from Public Data for Improving ASR Systems for Low-Resource Languages},
+  publisher = {arXiv},
+  year = {2022},
+  copyright = {arXiv.org perpetual, non-exclusive license}
+}
+```