Create README.md

README.md

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+---
+tags:
+- pyannote
+- audio
+- voice-activity-detection
+datasets:
+- dihard
+license: mit
+inference: false
+---
+
+## Example pyannote-audio Voice Activity Detection model 
+
+### `pyannote.audio.models.segmentation.PyanNet`
+
+♻️ Imported from https://github.com/pyannote/pyannote-audio-hub
+
+This model was trained by @hbredin.
+
+
+### Demo: How to use in pyannote-audio
+
+```python
+from pyannote.audio.core.inference import Inference
+
+model = Inference('julien-c/voice-activity-detection', device='cuda')
+model({
+	"audio": "TheBigBangTheory.wav"
+})
+```
+
+### Citing pyannote-audio
+
+```bibtex
+@inproceedings{Bredin2020,
+  Title = {{pyannote.audio: neural building blocks for speaker diarization}},
+  Author = {{Bredin}, Herv{\'e} and {Yin}, Ruiqing and {Coria}, Juan Manuel and {Gelly}, Gregory and {Korshunov}, Pavel and {Lavechin}, Marvin and {Fustes}, Diego and {Titeux}, Hadrien and {Bouaziz}, Wassim and {Gill}, Marie-Philippe},
+  Booktitle = {ICASSP 2020, IEEE International Conference on Acoustics, Speech, and Signal Processing},
+  Address = {Barcelona, Spain},
+  Month = {May},
+  Year = {2020},
+}
+```
+
+
+```bibtex
+@inproceedings{Lavechin2020,
+    author = {Marvin Lavechin and Marie-Philippe Gill and Ruben Bousbib and Herv\'{e} Bredin and Leibny Paola Garcia-Perera},
+    title = {{End-to-end Domain-Adversarial Voice Activity Detection}},
+    year = {2020},
+    url = {https://arxiv.org/abs/1910.10655},
+}```
+