Update README.md

README.md

@@ -16,4 +16,93 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+annotations_creators:
+- expert-generated
+license: mit
+multilinguality: []
+size_categories:
+- 10K<n<100K
+source_datasets: []
+task_categories:
+- audio-classification
+task_ids:
+- keyword-spotting
+pretty_name: FluSense
+tags:
+  - influenza
+  - audio-event
+  - flu
+  - cough
+  - sneeze
+  - classification
+  - health
 ---
+
+
+# FluSense
+
+**FluSense** is a dataset of segmented audio events derived from the FluSense platform, a contactless influenza-like illness surveillance system.
+
+This dataset is intended for use in flu symptom detection.
+
+## Dataset Structure
+
+Each sample includes:
+
+- `audio`: audio segment (waveform and sampling rate)
+- `label`: string label (e.g., "cough", "speech", etc.)
+
+## Labels
+
+The dataset includes the following sound event classes:
+
+- `cough`
+- `sneeze`
+- `sniffle`
+- `speech`
+- `silence`
+- `throat-clearing`
+- `burp`
+- `hiccup`
+- `gasp`
+- `breathe`
+
+*Excluded labels include: `vomit`, `wheeze`, `snore`, and `etc`.*
+
+## Source
+
+Segments were extracted from original FluSense recordings and aligned using expert-generated TextGrid annotations. Each `.wav` file corresponds to a labeled interval.
+
+## Use Cases
+
+- Influenza symptom detection
+- Syndromic surveillance modeling
+- Sound event detection in healthcare environments
+- Audio classification benchmarking
+
+## License
+
+This dataset is released under the **MIT License**.
+
+## Citation
+
+If you use this dataset, please cite the following work:
+
+```bibtex
+@article{10.1145/3381014,
+  author = {Al Hossain, Forsad and Lover, Andrew A. and Corey, George A. and Reich, Nicholas G. and Rahman, Tauhidur},
+  title = {FluSense: A Contactless Syndromic Surveillance Platform for Influenza-Like Illness in Hospital Waiting Areas},
+  year = {2020},
+  issue_date = {March 2020},
+  publisher = {Association for Computing Machinery},
+  address = {New York, NY, USA},
+  volume = {4},
+  number = {1},
+  url = {https://doi.org/10.1145/3381014},
+  doi = {10.1145/3381014},
+  journal = {Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.},
+  month = mar,
+  articleno = {Article 1},
+  numpages = {28},
+  keywords = {Contactless Sensing, Crowd Behavior Mining, Edge Computing, Influenza Surveillance}
+}