---
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()

```