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README.md

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+---
+license: cc-by-nc-4.0
+dataset_info:
+  features:
+  - name: audio
+    dtype: audio
+  - name: name
+    dtype: string
+---
+
+# WHAM!48kHz noise dataset
+
+This is a mirror of the [WHAM!48kHz noise dataset](http://wham.whisper.ai/).
+The original files were segmented and converted from WAV to Opus to reduce the size and accelerate streaming.
+
+- **Sampling rate**: 48 kHz
+- **Channels**: 2
+- **Format**: Opus
+- **Splits**:
+  - **Train**: 59 hours, 21216 segments, files 000 to 188
+  - **Validation**: 12 hours, 4444 segments, files 189 to 225
+  - **Test**: 7 hours, 2613 segments, files 226 to 249
+- **License:** CC BY-NC 4.0
+- **Source:** [http://wham.whisper.ai/](http://wham.whisper.ai/)
+- **Paper:** [WHAM!: Extending Speech Separation to Noisy Environments](https://arxiv.org/abs/1907.01160)
+
+## Usage
+
+```python
+import io
+
+import soundfile as sf
+from datasets import Features, Value, load_dataset
+
+for item in load_dataset(
+    "philgzl/wham",
+    split="train",
+    streaming=True,
+    features=Features({"audio": Value("binary"), "name": Value("string")}),
+):
+    print(item["name"])
+    buffer = io.BytesIO(item["audio"])
+    x, fs = sf.read(buffer)
+    # do stuff...
+```
+
+## Citation
+
+```bibtex
+@inproceedings{wichern2019wham,
+  title = {{WHAM!}: {Extending} speech separation to noisy environments},
+  author = {Wichern, Gordon and Antognini, Joe and Flynn, Michael and Zhu, Licheng Richard and McQuinn, Emmett and Crow, Dwight and Manilow, Ethan and Roux, Jonathan Le},
+  booktitle = INTERSPEECH,
+  pages = {1368--1372},
+  year = {2019},
+}
+```

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