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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
+---
+
+# EARS: Expressive Anechoic Recordings of Speech
+
+This is a mirror of the [Expressive Anechoic Recordings of Speech (EARS) dataset](https://github.com/facebookresearch/ears_dataset).
+The original files were converted from WAV to Opus to reduce the size and accelerate streaming.
+
+- **Sampling rate**: 48 kHz
+- **Channels**: 1
+- **Format**: Opus
+- **Splits**:
+  - **Train**: 92 hours, 15939 utterances, speakers p001 to p099
+  - **Validation**: 2 hours, 322 utterances, speakers p100 and p101
+  - **Test**: 6 hours, 966 utterances, speakers p102 to p107
+- **License:** CC BY-NC 4.0
+- **Source:** [github.com/facebookresearch/ears_dataset](https://github.com/facebookresearch/ears_dataset)
+- **Paper:** [EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberation](https://arxiv.org/abs/2406.06185)
+
+## Usage
+
+```python
+import io
+
+import soundfile as sf
+from datasets import Features, Value, load_dataset
+
+for item in load_dataset(
+    "philgzl/ears",
+    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{richter2024ears,
+  title = {{EARS}: {An} anechoic fullband speech dataset benchmarked for speech enhancement and dereverberation},
+  author = {Richter, Julius and Wu, Yi-Chiao and Krenn, Steven and Welker, Simon and Lay, Bunlong and Watanabe, Shinjii and Richard, Alexander and Gerkmann, Timo},
+  booktitle = INTERSPEECH,
+  pages = {4873--4877},
+  year = {2024},
+}
+```

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