Update README.md

README.md

@@ -12,7 +12,7 @@ tags:
 - Causal
 ---
 
-# Cadenza Challenge: CAD2-Task1
+# Cadenza Challenge: CAD2-Task2
 
 A Causal separation model for the CAD2-Task2 system.
 
@@ -55,4 +55,30 @@ model = DynamicSourceSeparator.from_pretrained(
 
 ```
 
+## Description
+
+Audio source separation model used in Sytem T002 for [Cadenza2 Task2 Challenge](https://cadenzachallenge.org/docs/cadenza2/Rebalancing%20Classical/rebalancing)
+
+The model is a finetune of the 8 ConvTasNet models from the Task2 baseline. 
+The training optimised the estimated sources and the recosntructed mixture
+
+$$
+  Loss = \sum_{}^{Sources}(L_1(estimated~source, ref~source)) + L_1(reconstructed~mixture, original~mixture)
+$$
+```Python
+def dynamic_masked_loss(mixture, separated_sources, ground_truth_sources, indicator):
+    # Reconstruction Loss
+    reconstruction = sum(separated_sources.values())
+    reconstruction_loss = nn.L1Loss()(reconstruction, mixture)
+    # Separation Loss
+    separation_loss = 0
+    for instrument, active in indicator.items():
+        if active:
+            separation_loss += nn.L1Loss()(
+                separated_sources[instrument], ground_truth_sources[instrument]
+            )
+    return reconstruction_loss + separation_loss
+```
+Model and T002 recipe are shared in [Clarity toolkit](https://github.com/claritychallenge/clarity)
+