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Technically, the following works:
But the results are not good. |
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Hello,
I have run the provided example in a file with two speakers and multiple emotional states.
However, this provides a single label.
On the other hand, I have this code that computes embeddings for each pyannote segment:
I was wondering if I could use a similar approach in order to predict emotions for each predefined segment.
So, the question is, instead of classifier.classify_file, is there a way to feed the waveform as above instead of a file?
Would classify_batch work with the above function?
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