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As a start I would suggest you extract embeddings with the model and use them as features to train some classifier, e.g. a SVM. This should give you an idea if the model is applicable to your problem. In a next step you could try to fine-tune the model on your data.
As a start I would suggest you extract embeddings with the model and use them as features to train some classifier, e.g. a SVM. This should give you an idea if the model is applicable to your problem. In a next step you could try to fine-tune the model on your data.
I have korean audio data sets which are labeled as depression and normal.
And each of them are at least 2 minutes.
Can I apply this model??
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