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---
language:
- en
license: apache-2.0
tags:
- hearing loss
- challenge
- signal processing
- source separation
- audio
- audio-to-audio
- Causal
---
# Cadenza Challenge: CAD2-Task1
A Causal Clarinet/Others separation model for the CAD2-Task2 baseline system.
* Architecture: ConvTasNet (Kaituo XU) with multichannel support (Alexandre Defossez).
* Parameters:
* B: 256
* C: 2
* H: 512
* L: 20
* N: 256
* P: 3
* R: 3
* X: 8
* audio_channels: 2
* causal: true
* mask_nonlinear: relu
* norm_type: cLN
* training:
* sample_rate: 44100
* samples_per_track: 64
* segment: 5.0
* aggregate: 2
* batch_size: 4
* early_stop: true
* epochs: 200
## Dataset
The model was trained using EnsembleSet and CadenzaWoodwind datasets.
## How to use
```
from tasnet import ConvTasNetStereo
model = ConvTasNetStereo.from_pretrained(
"cadenzachallenge/ConvTasNet_Clarinet_Causal"
).cpu()
```
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