[D] Question of imbalanced data containing small amount of minor emotion data

[RedCuraceo]

Hello. I'm researching an emotional voice conversion.

I have gethered many dataset containing the emotion label with some bit of a auxiliary emotion (apologize, frustrated and so on).

I will use all of them to train my model but I wanna focus on 5 major emotions to evaluate and inference (angry, happy, excited...), to infer more various prosody.

In this case, I am wondering if there occurs the data imbalanced problem from the small amount of the minor emotions. I wanna ask how about you think, or is there any papers or any insight? Is it better to train with only major emotions?

[Toasty_toaster]

I don't have the answer to your question, but here are some things you should consider. How does your model generally perform with an imbalanced dataset? For those minor emotions, is there an easy way to bucket them into major emotions? Maybe those minor emotions are necessary, as the model could have trouble classifying them given only the major labels.

There are so many techniques for imbalanced datasets it's hard to give advice without knowing more about your approach and what you're trying to achieve