rnnoise
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xiph
how to understand the cost ?
Hi,
As a new learner in deep learning, I'm a little puzzled about the cost definition,
def my_crossentropy(y_true, y_pred): return K.mean(2*K.abs(y_true-0.5) * K.binary_crossentropy(y_pred, y_true), axis=-1)
Could you please explain the function ?
Why 2*K.abs(y_true-0.5) * ?
and then the mymask
def mymask(y_true):
return K.minimum(y_true+1., 1.)
Why y_true+1. and then minimum ?
and
what's the mycost ?
Should have the mymask(y_true) * (10*K.square(K.square(K.sqrt(y_pred) - K.sqrt(y_true))) ?
and
what's in the my_accuracy ?
why 2*K.abs(y_true-0.5) ?
Thx
Hi,
As a new learner in deep learning, I'm a little puzzled about the cost definition,
def my_crossentropy(y_true, y_pred): return K.mean(2*K.abs(y_true-0.5) * K.binary_crossentropy(y_pred, y_true), axis=-1)Could you please explain the function ? Why
2*K.abs(y_true-0.5) *?and then the mymask
def mymask(y_true):return K.minimum(y_true+1., 1.)Whyy_true+1.and then minimum ?and what's the mycost ? Should have the
mymask(y_true) * (10*K.square(K.square(K.sqrt(y_pred) - K.sqrt(y_true)))?and what's in the my_accuracy ? why
2*K.abs(y_true-0.5)?Thx
The value of y_true for vad is 0,0.5,1. With y_true -0.5 operation, the value range can be tuned to -0.5~0.5. And the mask , it is used to mask some value which is -1.
HI, Please can anyone tell :- 1] Why the VAD values range is tuned between -0.5~0.5?
