Enhancing NLP for Romanized Bengali: Leveraging Knowledge Graphs, MoE Models, and Federated Learning

Meta Feature
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Hey fellow developers and linguists!

I've been exploring ways to improve NLP for Romanized Bengali, and I'd love to share my ideas and get your feedback.

The ChallengeRomanized Bengali is a common phenomenon, but it poses difficulties for NLP models due to its informal nature and lack of standardization.

Potential Solutions

  • Knowledge Graphs: Representing entities, concepts, and relationships in Romanized Bengali can help capture context and nuances.
  • MoE Models: Fine-tuning Mixture-of-Experts models can enable more accurate sentiment analysis, intent detection, and response generation.
  • Federated Learning: Leveraging user feedback through federated learning can help adapt models to individual user preferences and improve overall performance.

DiscussionI'd love to hear your thoughts on these ideas and any suggestions you might have! How can we work together to enhance NLP for Romanized Bengali?

Tags

  • NLP
  • Romanized Bengali
  • Knowledge Graphs
  • MoE Models
  • Federated Learning


Discuss this on our forum.
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Hi and welcome to our community! This forum is specific to Discourse, the open source software product. You are welcome to participate here but it has to be related to Discourse.

We do use AI here so you are welcome to follow topics on AI. See the #ai tag and https://discourse.org/ai.

We also have people in the community working to translate Discourse into Bengali, though I am not certain of the status. You're welcome to contribute to those efforts!

You could start here: https://meta.discourse.org/t/add-a-bengali-translation-to-discourse/173844?u=tobiaseigen



Discuss this on our forum.