You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I found that there exist experiments of PHOENIX-2014T and CSL-daily and the model architecture is based on Sign2(Gloss+Text).
The sign2 (Gloss+Text) model uses features generated by pretrained spatial embeddings, but there is no feature pickle in the csl-daily dataset. It would be appreciated if you could tell us how the features created by csl-daily were obtained.
The text was updated successfully, but these errors were encountered:
I found that there exist experiments of PHOENIX-2014T and CSL-daily and the model architecture is based on Sign2(Gloss+Text). The sign2 (Gloss+Text) model uses features generated by pretrained spatial embeddings, but there is no feature pickle in the csl-daily dataset. It would be appreciated if you could tell us how the features created by csl-daily were obtained.
We use the features from the file Extracted_Features_with_BN-TIN-Transformer.zip in the CSL-Daily dataset.
Thank you for your research.
I found that there exist experiments of PHOENIX-2014T and CSL-daily and the model architecture is based on Sign2(Gloss+Text).
The sign2 (Gloss+Text) model uses features generated by pretrained spatial embeddings, but there is no feature pickle in the csl-daily dataset. It would be appreciated if you could tell us how the features created by csl-daily were obtained.
The text was updated successfully, but these errors were encountered: