Update README.md

README.md

@@ -104,4 +104,65 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- automatic-speech-recognition
+language:
+- fr
+tags:
+- medical
+pretty_name: PxCorpus
+size_categories:
+- 1K<n<10K
 ---
+
+# PxCorpus : A Spoken Drug Prescription Dataset in French
+
+PxCorpus is to the best of our knowledge, the first spoken medical drug prescriptions corpus to be distributed. 
+It contains 4 hours of transcribed and annotated dialogues of drug prescriptions in 
+French acquired through an experiment with 55 participants experts and non-experts  in drug prescriptions.
+
+The automatic transcriptions were verified by human effort and aligned with 
+semantic labels to allow training of NLP models. The data acquisition protocol 
+was reviewed by medical experts and permit free distribution without breach of 
+privacy and regulation. 
+
+## Overview of the Corpus
+The experiment has been performed in wild conditions with naive participants and medical experts.
+In total, the dataset includes 2067 recordings of 55 participants (38% non-experts,
+25% doctors, 36% medical practitioners), manually transcribed and semantically annotated.
+
+| Category         | Sessions | Recordings | Time(m)|
+|------------------| -------- | ---------- | ------ |
+| Medical experts  |   258    |    434     |  94.83 |
+| Doctors          |   230    |    570     | 105.21 |
+| Non experts      |   415    |    977     |  62.13 |
+| Total            |   903    |   1981     | 262.27 |
+
+## License
+We hope that that the community will be able to benefit from the dataset  
+which is distributed with an attribution 4.0 International (CC BY 4.0) Creative Commons licence.
+
+## How to cite this corpus
+
+If you use the corpus or need more details please refer to the following paper: A spoken drug prescription datset in French for spoken Language Understanding
+
+@InProceedings{Kocabiyikoglu2022,
+  author = 	"Alican Kocabiyikoglu and Fran{\c c}ois Portet and Prudence Gibert and Hervé Blanchon and Jean-Marc Babouchkine and Gaëtan Gavazzi",
+  title = 	"A spoken drug prescription datset in French for spoken Language Understanding",
+  booktitle = 	"13th Language Ressources and Evaluation Conference (LREC 2022)",
+  year = 	"2022",
+  location = 	"Marseille, France"
+}
+
+
+## Dataset features
+
+* `path` -- Audio name
+* `text` -- Audio utterance
+* `ner` -- Semantic annotation from the original dataset
+* `speaker_id` -- Speaker ID
+* `speaker_age_range` -- Speaker age range
+* `speaker_gender` -- Speaker gender
+* `speaker_category` -- Speaker category (doctor, expert, non-expert)
+* Other column names are for the occurences of each NER tag, could be useful for computing some metrics