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enhancementNew feature or requestNew feature or request
Description
As shown in the docs, we can handle models that have different heads for different sexes, e.g.
def f0(signal, sampling_rate, idx, gender, f0_range):
# extract mean f0 using a gender adapted range
y = librosa.yin(
signal,
fmin=f0_range[gender[idx]][0],
fmax=f0_range[gender[idx]][1],
sr=sampling_rate,
).mean()
return y, gender[idx]
interface = audinterface.Feature(
['f0', 'gender'],
process_func=f0,
process_func_args={
'gender': gender,
'f0_range': f0_range,
},
)
The problem is that the gender
argument is not really static but depends on the input data.
To update it you would need to create a new Feature
object for each new database, which is not what we want for ONNX models, or you could update the process_func_args
, which is ok, but they are hidden under interface.process.process_func_args
.
So maybe we update the documentation by showing an example how to update them?
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enhancementNew feature or requestNew feature or request