Create README.md

README.md

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+---
+license: apache-2.0
+dataset_info:
+  features:
+  - name: hypothesis
+    sequence: string
+  - name: transcription
+    dtype: string
+  - name: input1
+    dtype: string
+  - name: hypothesis_concatenated
+    dtype: string
+  - name: source
+    dtype: string
+  - name: id
+    dtype: string
+  - name: dummy_str
+    dtype: string
+  - name: dummy_list
+    sequence: 'null'
+  - name: prompt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 469086507
+    num_examples: 286366
+  - name: test
+    num_bytes: 24103011
+    num_examples: 18237
+  download_size: 125101353
+  dataset_size: 493189518
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: test
+    path: data/test-*
+---
+
+# Dataset Name: Pilot dataset for Multi-domain ASR corrections
+
+<p align="center">  <img src="hypilot.jpg" height ="100"> </p>
+
+
+## Description
+
+This dataset is a pilot version of a larger dataset for automatic speech recognition (ASR) corrections across multiple domains. 
+It contains paired hypotheses and corrected transcriptions for various ASR tasks consolidated from [PeacefulData/HyPoradise-v0](https://huggingface.co/datasets/PeacefulData/HyPoradise-v0)
+
+## Structure
+
+### Data Split
+
+The dataset is divided into training and test splits:
+
+- Training Data: 281,082 entries
+  - Approximately 6,255,198 tokens for transcriptions
+  - Approximately 31,211,083 tokens for concatenated hypotheses
+- Test Data: 16,108 entries
+  - Approximately 327,750 tokens for transcriptions
+  - Approximately 1,629,093 tokens for concatenated hypotheses
+
+### Columns
+
+- `hypothesis`: N-best hypothesis from beam search.
+- `transcription`: Corrected asr transcription.
+- `hypothesis_concatenated`: An alternative version of the text output.
+- `source`: The source of the text entry, indicating the origin dataset.
+- `prompt`: Instructional prompt for correction task
+- `score`: An acoustic model score (not all entries have this).
+
+### Source Datasets
+
+The dataset combines entries from various sources:
+
+- **Training Sources**:
+  - `train_td3`: 50,000 entries
+  - `train_other_500`: 50,000 entries
+  - `train_cv`: 47,293 entries 
+  - `train_lrs2`: 42,940 entries
+  - `train_wsj_score`: 37,514 entries
+  - `train_swbd`: 36,539 entries
+  - `train_chime4`: 9,600 entries
+  - `train_atis`: 3,964 entries
+  - `train_coraal`: 3,232 entries
+- **Test Sources**:
+  - `test_ls_other`: 2,939 entries
+  - `test_ls_clean`: 2,620 entries
+  - `test_lrs2`: 2,259 entries
+  - `test_swbd`: 2,000 entries
+  - `test_cv`: 2,000 entries
+  - `test_chime4`: 1,320 entries
+  - `test_td3`: 1,155 entries  
+  - `test_wsj_score`: 836 entries
+  - `test_atis`: 809 entries
+  - `test_coraal`: 170 entries
+
+
+## Access
+
+The dataset can be accessed and downloaded through the HuggingFace Datasets library. Use the following command to load the dataset:
+
+```python
+from datasets import load_dataset
+dataset = load_dataset("PeacefulData/HyPoradise-pilot")
+```
+
+## Acknowledgments
+
+This dataset is consolidated from the PeacefulData/HyPoradise-v0 dataset. Thanks to the original creators for making this data available.
+
+### References
+
+```bib
+@inproceedings{yang2023generative,
+  title={Generative speech recognition error correction with large language models and task-activating prompting},
+  author={Yang, Chao-Han Huck and Gu, Yile and Liu, Yi-Chieh and Ghosh, Shalini and Bulyko, Ivan and Stolcke, Andreas},
+  booktitle={2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)},
+  pages={1--8},
+  year={2023},
+  organization={IEEE}
+}
+```
+
+```bib
+@inproceedings{chen2023hyporadise,
+  title={HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models},
+  author={CHEN, CHEN and Hu, Yuchen and Yang, Chao-Han Huck and Siniscalchi, Sabato Marco and Chen, Pin-Yu and Chng, Ensiong},
+  booktitle={Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
+  year={2023}
+}
+```