Can you clarify the question here?

I do not think that the acoustical signature of genders is one -to-one and for example you can try in your DL/ML/AI based classifier that you will have outliers for the transgender case. try it and then do let me know. Speech recognition needs to be used carefully with zero false rate alarms to be useful otherwise it is the same situation in medical emergency rooms where the wrong diagnostics creates worse problems..Wrong Diagnosis is a serious mistake with serious ramifications ..

Generally masculine.

Slightly changed