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Language Detector

Detect the language of any text in seconds, free online

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AI Language Detector

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What language is that support ticket actually written in? Is the whole message in one language, or does it switch halfway through the second paragraph? Language Detector reads text and identifies the language, the script and how confident it is about either.

What is Language Detector?

Language Detector answers a question that sounds trivial and often is not. A long paragraph of clear French is easy. Three words in a review, a product name surrounded by two languages, or a message that switches between them mid sentence is much harder, and those are the cases that actually arrive in a support queue.

The detection scope options exist for exactly that. You can ask for one verdict on the whole document, a verdict per sentence, a check for code switching, or a dialect and variant identification rather than just the language family.

How Does Language Detector Work?

Paste the text whose language you want identified. Short snippets are supported, and the Short Snippet scope exists because a handful of words needs different handling from a page.

Set the scope and the confidence mode, then generate. The verdict arrives in the output card, ready to copy into whichever system needed the answer, and every check from your session stays in the activity history if you are working through a queue of messages one at a time.

What works well

  • Handles mixed language text rather than forcing one answer
  • Reports confidence, so a weak guess is visible as a weak guess
  • Identifies the writing system as well as the language
  • Dialect and variant detection goes beyond naming the language family

What to watch for

  • Very short text is genuinely ambiguous, and no tool solves that reliably
  • Closely related languages are the usual source of a wrong answer
  • Proper nouns and brand names can pull a verdict towards the wrong language

Who Should Use It?

Support teams routing tickets to the right agent. Researchers sorting a corpus gathered from several countries. Localisation managers auditing which languages already exist in a content set. Developers testing what their own detection logic does with awkward input before it reaches production.

OptionWhat it controlsSuggested value
Detection ScopeWhether one verdict or many are returnedWhole Document for routing, Per-Sentence for mixed text
Confidence ModeHow cautious the answer isBalanced, or Show All Candidates when the text is short
Output DetailHow much comes back with the verdictLanguage + Confidence for automation, Full Report for analysis
Fallback ModeWhat happens when nothing is certainMark as Undetermined, which is safer than a confident guess

Note Set Fallback Mode to Mark as Undetermined when the verdict feeds an automated process. A message routed to the wrong team on a low confidence guess costs more than one flagged for a human to look at.

Where The Answer Earns Its Keep

Detection is rarely the goal in itself. It is the step that decides where something goes next: which translator, which queue, which reading pile. Getting it right saves a handoff, and getting it wrong usually costs two. For a long document where you also need to know what it says before deciding who handles it, the Text Summarizer is the useful second step once the language is known.

You never create an EizTools account and never watch a balance, which suits a queue of a hundred short messages. Language Detector also lets you pick the AI model family, and that is worth doing for text in less widely written languages, where families differ noticeably in coverage.

Frequently Asked Questions

How short can the text be?

A few words often work, and confidence drops quickly as text gets shorter. Use the Short Snippet scope and Show All Candidates so you see the alternatives rather than one uncertain answer.

Can it detect more than one language in a message?

Yes. Turn on mixed language detection and set the scope to Per-Sentence. That is the right configuration for messages that switch languages partway through.

Does it identify dialects?

To an extent. The Dialect/Variant scope distinguishes regional forms where the written differences are real. Where two variants are written almost identically, no text based method can separate them.

Why does it sometimes get it wrong?

Usually because the languages are closely related or the sample is very short. Raising the sensitivity setting and asking for alternative candidates shows you how close the second guess was.

Knowing what language something is in sounds like a solved problem until you meet a two word review or a bilingual complaint. Paste the text above, pick a scope that matches how mixed you expect it to be, and let an uncertain answer be reported as uncertain rather than dressed up as a decision.

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