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The Performance of the new models are bad for specific languages #41

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Respaired opened this issue Jul 30, 2024 · 3 comments
Open

The Performance of the new models are bad for specific languages #41

Respaired opened this issue Jul 30, 2024 · 3 comments

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@Respaired
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Respaired commented Jul 30, 2024

Thank you for creating e2v. how can i access the previous model that could only output a few labels instead of 9?
I find this new ckpt (the plus large) to be so much worse compared to the old one at least for Persian.

the model also hallucinates a lot with short inputs (1-2 seconds) even in English.

@ddlBoJack
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You can modify the logits to specific emotions(such as 5) by masking the emotions you don't need. You will get similar performance with the previous model.

@buanide
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buanide commented Aug 8, 2024

If I use the feature vectors ('feats') generated by the Automodel library's model.generate function on audio files as input to train a new model for Speech emotion recognition, is this process equivalent to fine-tuning or training a downstream model for speech emotion recogniton ? Are these features equivalent to embeddings or raw audio features ?

@ddlBoJack
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If I use the feature vectors ('feats') generated by the Automodel library's model.generate function on audio files as input to train a new model for Speech emotion recognition, is this process equivalent to fine-tuning or training a downstream model for speech emotion recogniton ? Are these features equivalent to embeddings or raw audio features ?

I did not get your idea clearly. We provide emotion2vec for extracting features and emotion2vec+ for classification. And both types of the model provide embeddings for further exploration of your tasks.

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