xiph/rnnoise

How to evaluate the performance of denoising when i Compared two weights?

wangohaha opened this issue · 4 comments

wangohaha commented

i trained two weights of the rnnoise.
when i tested the wav by myself, each ones all got a good denoising performance.
However , i do not know which one is the best ?
so, do you know some ways to evaluate the performance of denoising or the code to evaluate the performance of denoising wavs?

jagger2048 commented

Hi,
You can use the PESQ to evaluate the output of the two weights.
python-pesq

B&R

wangohaha commented

ok,3q
however when i use pypesq , i had a problem of the usage;
the ref signal is the data before mixing noise or the data after mixing noise

guishengzhang commented

The ref signal should be clean speech before mixing noise.

RXAldreezee commented

Hi,
You can use the PESQ to evaluate the output of the two weights.
python-pesq

B&R

I agree with this. Make sure you have clean wav file and rnnoise-processed wav file. Produce a wav file in each of the model and use the python-pesq to compare. All wav files should have the same audio duration and 16k sampling frequency.

If its doesn't work, try https://github.com/schmiph2/pysepm