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About IEMOCAP sentence-level audio features #3
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Hello, |
We used openSMILE and then fed that to an FC network with 100-dim output. This FC network can be trained using your training dataset's labels. Alternatively you can use other audio features as shown here: https://github.com/soujanyaporia/MUStARD |
Hi, thanks for your clarification. Could you please share the scripts of dimension reduction process? I am trying to replicate the feature extraction but having trouble with the FC network settings for dimension reduction. BTW, may I know why the librosa feature are with different size for each audio utterance? Thank you! |
Hello,
Can you share the way you extract audio features in the work "Multi-level Multiple Attentions for Contextual Multimodal Sentiment Analysis"? I have no idea that how to extract 100 dimensions sentence-level audio features.
Thank you !
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