Create README.md

README.md

@@ -1,25 +1,56 @@
 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: int32
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 16000
-  - name: text_gl
-    dtype: string
-  - name: text_en
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 2350499131.6252074
-    num_examples: 3450
-  download_size: 2338691367
-  dataset_size: 2350499131.6252074
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+task_categories:
+- translation
+- automatic-speech-recognition
+language:
+- gl
+- en
+size_categories:
+- 1K<n<10K
 ---
+# Dataset Details
+
+**FLEURS-SpeechT-GL-EN** is Galician-to-English dataset for Speech Translation task.
+
+This dataset has been compiled from Google's **[FLEURS data set](https://huggingface.co/datasets/google/fleurs)**
+It contains ~10h11m of galician audios along with its text transcriptions and the correspondant English translations.
+
+# Preprocessing
+
+This dataset has been generated based on Google's FLEURS speech dataset, by aligning English and Galician data.
+The alignment process has been performed following **[ymoslem's FLEURS dataset processing script](https://github.com/ymoslem/Speech/blob/main/FLEURS-GA-EN.ipynb)**
+
+### English translations quality
+
+To get a sense of the quality of the english text with respect to the galician transcriptions, a Quality Estimation model has been applied.
+
+- **QE model**: [Unbabel/wmt23-cometkiwi-da-xl](https://huggingface.co/Unbabel/wmt23-cometkiwi-da-xl)
+- **Average QE score**: 0.76
+
+# Dataset Structure
+
+```
+DatasetDict({
+    train: Dataset({
+        features: ['id', 'audio', 'text_gl', 'text_en'],
+        num_rows: 3450
+    })
+})
+```
+
+# Citation
+
+```
+@article{fleurs2022arxiv,
+  title = {FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech},
+  author = {Conneau, Alexis and Ma, Min and Khanuja, Simran and Zhang, Yu and Axelrod, Vera and Dalmia, Siddharth and Riesa, Jason and Rivera, Clara and Bapna, Ankur},
+  journal={arXiv preprint arXiv:2205.12446},
+  url = {https://arxiv.org/abs/2205.12446},
+  year = {2022},
+```
+
+Yasmin Moslem preprocessing script: https://github.com/ymoslem/Speech/blob/main/FLEURS-GA-EN.ipynb
+
+## Dataset Card Contact
+
+Juan Julián Cea Morán (jjceamoran@gmail.com)