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The problem with standard tokenizers

This story is from 2026-10-15. It is preserved in the archive; the latest stories are on the live feed.

The problem with standard tokenizers If you have ever tried running a standard NLP tokenizer over Roman Urdu text, you know it falls apart fast. Words like "kyunnn", "kese ho", or "btao" break the assumptions that most tokenizers are built on: consistent spelling, a stable lexicon, clean word bound…

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  1. 2026-10-15 12:50 · DEV Community — AI
    The problem with standard tokenizers

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