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README.md

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+---
+license: cc-by-4.0
+dataset_info:
+  features:
+  - name: audio
+    dtype: audio
+  - name: name
+    dtype: string
+configs:
+  - config_name: default
+    data_files:
+      - split: speech_english
+        path: data/speech-english-*.parquet
+      - split: speech_french
+        path: data/speech-french-*.parquet
+      - split: speech_german
+        path: data/speech-german-*.parquet
+      - split: speech_italian
+        path: data/speech-italian-*.parquet
+      - split: speech_russian
+        path: data/speech-russian-*.parquet
+      - split: speech_spanish
+        path: data/speech-spanish-*.parquet
+      - split: noise
+        path: data/noise-*.parquet
+      - split: rir_slr26
+        path: data/rir-slr26-*.parquet
+      - split: rir_slr28
+        path: data/rir-slr28-*.parquet
+---
+
+# DNS5 Challenge data
+
+This is a mirror of the [DNS5 Challenge data](https://github.com/microsoft/DNS-Challenge/).
+The original files were converted from WAV to Opus to reduce the size and accelerate streaming.
+
+⚠️ Only the LibriVox, AudioSet, Freesound, OpenSLR26, and OpenSLR28 data is included. The VCTK, VocalSet, CREMA-D, VoxCeleb2, and DEMAND data is excluded. ⚠️
+
+- **Sampling rate**: 48 kHz
+- **Channels**: 1
+- **Format**: Opus
+- **Splits**:
+  - **speech_english**: 245 hours, 186743 files
+  - **speech_french**: 95 hours, 60454 files
+  - **speech_german**: 137 hours, 119175 files
+  - **speech_italian**: 70 hours, 59525 files
+  - **speech_russian**: 25 hours, 16566 files
+  - **speech_spanish**: 86 hours, 78603 files
+  - **noise**: 177 hours, 63810 files
+  - **rir_slr26**: 17 hours, 60000 files
+  - **rir_slr28**: 0.1 hours, 248 files
+- **License:**
+  - **LibriVox**: [Public domain](https://librivox.org/pages/public-domain/)
+  - **AudioSet**: CC BY 4.0
+  - **Freesound**: CC0 1.0
+  - **OpenSLR26 and OpenSLR28**: Apache 2.0
+- **Source:** [https://github.com/microsoft/DNS-Challenge/](https://github.com/microsoft/DNS-Challenge/)
+- **Paper:** [ICASSP 2023 Deep Noise Suppression Challenge](https://arxiv.org/abs/2303.11510)
+
+## Usage
+
+```python
+import io
+
+import soundfile as sf
+from datasets import Features, Value, load_dataset
+
+for item in load_dataset(
+    "philgzl/dns5",
+    split="speech_english",
+    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
+@article{dubey2024icassp,
+  title = {{ICASSP} {2023} {Deep} {Noise} {Suppression} {Challenge}},
+  author = {Dubey, Harishchandra and Aazami, Ashkan and Gopal, Vishak and Naderi, Babak and Braun, Sebastian and  Cutler, Ross and Gamper, Hannes and Golestaneh, Mehrsa and Aichner, Robert},
+  journal = {IEEE Open J. Signal Process.},
+  volume = {5},
+  pages = {725--737},
+  year = {2024},
+}
+```

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