Update README.md

README.md

@@ -1,3 +1,90 @@
+---
+pretty_name: "Medical Questionnaire: Multilingual Translation"
+license: other
+language:
+  - fr
+  - sq
+  - ar
+  - ary
+  - aeb
+  - arq
+  - prs
+  - fa
+  - ru
+  - en
+  - es
+  - ti
+  - uk
+tags:
+  - text
+  - tabular
+  - medical
+  - healthcare
+  - multilingual
+  - low-resource
+  - translation
+  - UMLS
+task_categories:
+  - translation
+task_ids:
+  - machine-translation
+multilinguality: multilingual
+dataset_type: text
+size_categories:
+  - 10K<n<100k
+configs:
+  - config_name: default
+    data_files:
+      - translations.csv
+dataset_info:
+  features:
+    - name: sentence_id
+      dtype: int64
+    - name: src_lang
+      dtype: string
+    - name: tgt_lang
+      dtype: string
+    - name: gender_variant
+      dtype: string
+    - name: source_text
+      dtype: string
+    - name: target_text
+      dtype: string
+    - name: semantic_gloss
+      dtype: string
+    - name: CUI_semantic_gloss
+      dtype: string
+  splits:
+    - name: train
+      num_examples: null
+  citation: |
+    If you use the translations, please cite:
+      @inproceedings{bouillon-etal-2021-speech,
+        title = "A Speech-enabled Fixed-phrase Translator for Healthcare Accessibility",
+        author = "Bouillon, Pierrette and Gerlach, Johanna and Mutal, Jonathan and Tsourakis, Nikos and Spechbach, Herv{\'e}",
+        booktitle = "Proceedings of the 1st Workshop on NLP for Positive Impact",
+        month = aug,
+        year = "2021",
+        publisher = "Association for Computational Linguistics",
+        url = "https://aclanthology.org/2021.nlp4posimpact-1.15/",
+        doi = "10.18653/v1/2021.nlp4posimpact-1.15",
+        pages = "135--142"
+      }
+      @article{info:doi/10.2196/13167,
+        author="Spechbach, Herv{\'e} and Gerlach, Johanna and Mazouri Karker, Sanae and Tsourakis, Nikos and Combescure, Christophe and Bouillon, Pierrette",
+        title="A Speech-Enabled Fixed-Phrase Translator for Emergency Settings: Crossover Study",
+        journal="JMIR Med Inform",
+        year="2019",
+        month="May",
+        volume="7",
+        number="2",
+        pages="e13167",
+        doi="10.2196/13167"
+      }
+paper: null
+---
+
+
 # Diagnostic Interview Corpus
 
 The **Diagnostic interview corpus** is a multilingual dataset of **12,754 French medical diagnostic interview sentences** (questions and instructions) with translations into 12 target languages and a **semantic gloss based on UMLS (Unified Medical Language System)**.