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I am trying to implement the paper: https://arxiv.org/pdf/1710.10468.pdf to create an unsupervised diarization algorithm using the d-vectors provided by the pre-trained model in Resemblyzer.
I found that the length of the partial utterances (1.6s), determined by the hyperparameter partials_n_frames with a default value 160 may be too high. In the paper, the authors recommend a window size and step of 240ms and 120ms for this kind of diarization, respectively.
Is this parameter something that can be changed easily? As it is implemented as a setting in the source (hyperparams.py) code and not as an argument of a function or method it looks like it is not a good idea to modify it.
Thanks in advance.
David.
The text was updated successfully, but these errors were encountered:
I have the same question as I had resolution issues while implementing the same paper. I'm a little confused why partials_n_fames isn't a changeable parameter. Have you tried changing it?
Who said the partials_n_fames can not be changed? If my partial utterance duration is 400ms (default is 1.6 seconds), I would make the rate to be 2.5 and then change the value of partials_n_frames = 40, so that mel_window_step * partials_n_frames == partial utterance duration
Hi!
I am trying to implement the paper: https://arxiv.org/pdf/1710.10468.pdf to create an unsupervised diarization algorithm using the d-vectors provided by the pre-trained model in Resemblyzer.
I found that the length of the partial utterances (1.6s), determined by the hyperparameter
partials_n_frames
with a default value 160 may be too high. In the paper, the authors recommend a window size and step of 240ms and 120ms for this kind of diarization, respectively.Is this parameter something that can be changed easily? As it is implemented as a setting in the source (
hyperparams.py
) code and not as an argument of a function or method it looks like it is not a good idea to modify it.Thanks in advance.
David.
The text was updated successfully, but these errors were encountered: