shithub: opus

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more emphasis on pitch loss

--- a/dnn/training_tf2/train_plc.py

+++ b/dnn/training_tf2/train_plc.py

@@ -103,7 +103,7 @@

         y_true = y_true[:,:,:-1]

         e = (y_pred - y_true)*mask

         e_bands = tf.signal.idct(e[:,:,:-2], norm='ortho')

-        l1_loss = K.mean(K.abs(e)) + bias*K.mean(K.maximum(e[:,:,:1], 0.)) + alpha*K.mean(K.abs(e_bands) + bias*K.maximum(e_bands, 0.))

+        l1_loss = K.mean(K.abs(e)) + bias*K.mean(K.maximum(e[:,:,:1], 0.)) + alpha*K.mean(K.abs(e_bands) + bias*K.maximum(e_bands, 0.)) + 5*K.mean(K.minimum(K.abs(e[:,:,18:19]),1.))

         return l1_loss

     return loss

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