Why is the speech signal not convolutional mixing

[bbbgan]

Hello, fakufaku, thanks for your amazing work!
I have just started exploring BSS and I have a question. Why is the signal not convolutional mixed?
It seems like linear mixed. Isn't this contradictory to the theory of IVA? IVA requires convolutional mixing in the time domain and linear mixing in the frequency domain.
this is the mixing code:

auxiva-ipa/room_builder.py

Line 198 in ec9d17c

mix = np.sum(premix[:n_tgt, :], axis=0) + bg + un

I have been troubled by this issue for a long time. You are an expert in this field, can you give me some advices?

[fakufaku]

Hi @bbbgan , you are right that IVA is designed to handle convolutional mixtures.
In the code you point out, the array premix contains all the source signals already convolved with the appropriate impulse responses. So the resulting mixture is indeed convolutional.

[bbbgan]

Appreciate for your reply, the si_bss_eval in convergence_callback is seems to evaluate the performance of the IVA. However, it evaluates the ref_sig[:n_targets, :m].T and the result synth[:-1, :m].T, the ref_sig[:n_targets, :m].T is come from the premix as following codes:

auxiva-ipa/simulation_loop.py

Line 114 in ec9d17c

refs[:n_targets, :] = premix[:n_targets, parameters["mix_params"]["ref_mic"], :]

So I'm confused. why compare the premix rather than the original signal with the results

auxiva-ipa/room_builder.py

Line 149 in ec9d17c

sdr, sir, sar, perm = si_bss_eval(ref_sig[:, :m].T, synth[:, :m].T)

[fakufaku]

IVA will separate the reverberant signals without doing reverberation. It is thus correct to compare to the reverberant isolated signal rather than the anechoic original signal.

[bbbgan]

Reverberation will introduce dependencies between the signals, so it is correct. But one more question, if we evaluate the premix and the results, the mix is linear mixed by the premix. It's not convolutional mixing.
So it seems like IVA separating the mix which is linear mixed by original signal premix