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README.md

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+---
+tags:
+- asteroid
+- audio
+- FasNet-TAC
+- audio-source-separation
+- multichannel
+- beamforming
+datasets:
+- TACDataset
+- sep_noisy
+license: cc-by-sa-3.0
+inference: false
+---
+
+## Asteroid model `Samuele Cornell/FasNetTAC_TACDataset_separatenoisy`
+Imported from [Zenodo](https://zenodo.org/record/4557489)
+
+### Description:
+This model was trained by popcornell using the TAC/TAC recipe in Asteroid. It was trained on the separate_noisy task of the TACDataset dataset.
+
+### Training config:
+```yaml
+data:
+    dev_json: ./data/validation.json
+    sample_rate: 16000
+    segment: None
+    test_json: ./data/test.json
+    train_json: ./data/train.json
+net:
+    chunk_size: 50
+    context_ms: 16
+    enc_dim: 64
+    feature_dim: 64
+    hidden_dim: 128
+    hop_size: 25
+    n_layers: 4
+    n_src: 2
+    window_ms: 4
+optim:
+    lr: 0.001
+    weight_decay: 1e-06
+training:
+    accumulate_batches: 1
+    batch_size: 8
+    early_stop: True
+    epochs: 200
+    gradient_clipping: 5
+    half_lr: True
+    num_workers: 8
+    patience: 30
+    save_top_k: 10
+```
+
+### Results:
+```yaml
+si_sdr: 10.871864315894744
+si_sdr_imp: 11.322284052560262
+```
+
+### License notice:
+This work "FasNetTAC_TACDataset_separatenoisy" is a derivative of LibriSpeech ASR corpus by Vassil Panayotov, used under CC BY 4.0; of End-to-end Microphone Permutation and Number Invariant Multi-channel Speech Separation by Yi Luo, Zhuo Chen, Nima Mesgarani, Takuya Yoshioka, used under CC BY 4.0. "FasNetTAC_TACDataset_separatenoisy" is licensed under Attribution-ShareAlike 3.0 Unported by popcornell.
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