Tracing correct words from Jumbled words using machine learning

Click For Summary
Machine learning can potentially trace correct words from jumbled letters, but simpler methods like permuting letters and querying a dictionary may suffice. Users express frustration with existing spell checkers and auto-correct features that often misinterpret or replace intended words. The discussion highlights concerns about the limitations of machine learning in this context, suggesting it may not significantly improve upon current solutions. There is skepticism about the necessity of machine learning for this task, as traditional algorithms could achieve similar results. Overall, the conversation emphasizes the need for more user-friendly and accurate text correction tools.
akerkarprashant
Messages
74
Reaction score
10
TL;DR
Tracing correct words from Jumbled words using machine learning prediction, search algorithms.
Can we trace all correct words from Jumbled words using machine learning prediction, search algorithms?

https://builtin.com/machine-learning/nlp-machine-learning

Input Dataset : Jumbled words.

Jumbled word example: oolp

Output : pool, loop, polo.
 

Attachments

  • images (4).gif
    images (4).gif
    7.4 KB · Views: 175
Last edited:
Computer science news on Phys.org
Not sure you’d need machine learning to do this. I’d permute the letters and query a dictionary to determine if it’s a valid word.
 
  • Like
Likes akerkarprashant, anorlunda and pbuk
YIKES! Not another aggressive spell checker.

Given a set of scrambled letters, it may be possible to find a long list of dictionary words. So the spell checker chooses the one it "thinks" best from the list and replaces my text. Or the machine learning checker chooses the most common word from its training data and replaces my text. It is so frustrating to have all the spell checkers over the years refuse to allow me to type my own name -- Dick. :mad:
 
  • Like
Likes akerkarprashant
Isn't this just a slightly inferior version of that auto-correct/complete feature present in most phone messaging applications?
 
LLMs and AIs have a bad reputation at PF, and I share this opinion. I have seen too much nonsense they produced, and too many "independent researchers" who weren't so independent after all, since they used them. And then there is a simple question: If we had to check their results anyway, why would we use them in the first place? In fact, their use is forbidden by the rules. I tend to interpret the reason for this rule because nobody wants to talk to a machine via PF. Those who want to can...