AI Search (GEO)
Khmer Token Density Analyzer
Khmer has no spaces — so AI systems segment it into syllables and tokens. Analyze your Khmer text the way an LLM sees it: word tokens, syllable clusters, top keyword density and estimated token counts. Optimise Khmer-language content for AI search and translation quality.
Loading tool…
Need reliable hosting, a domain, or a hand setting this up?
Get a free quote →About the Khmer Token Density Analyzer
The Khmer Token Density Analyzer is a rare tool built specifically for Khmer-language content: it segments Khmer script — which is written without spaces between words — into words and syllable clusters using your browser's built-in Khmer segmentation engine. Paste Khmer or mixed Khmer/English text and get instant tiles for Khmer words, syllable clusters, Khmer characters, Latin words and an approximate LLM token count, plus a chip cloud of your 15 most frequent Khmer word tokens with counts and density percentages.
This free tool by Hosting Cambodia exists because Khmer SEO is different: search engines and AI systems must segment Khmer themselves, and how often your key tokens — product names, city names like Phnom Penh and Siem Reap, service terms — naturally repeat directly shapes topical relevance. Khmer also consumes far more LLM tokens per sentence than English, which affects AI context limits and API costs. Businesses writing for Cambodia's Khmer-speaking market can use the analyzer to check keyword density and token budgets before publishing, entirely client-side with no text ever leaving the browser.
Frequently asked questions
How does the tool split Khmer text without spaces?
It uses the browser's built-in Intl.Segmenter with the Khmer locale — the same class of dictionary-based segmentation search engines use — to find word boundaries, and grapheme segmentation to count syllable clusters. Recent versions of Chrome, Edge and Safari support it fully.
Why do Khmer texts use so many more LLM tokens than English?
Khmer script is encoded with stacked consonants, vowel signs and diacritics, and most tokenizers were trained mainly on English, so a Khmer sentence can cost several times the tokens of its English translation. The tool approximates this as one token per syllable cluster plus 1.3 per Latin word.
How does token density help my Khmer SEO?
The top-tokens list shows which Khmer words dominate your text. If your main service, product or location terms rank high with a healthy density, the page signals clear topical relevance for Khmer searches; if they barely appear, work them in naturally before publishing.
Explore the full free web tools toolbox by Hosting Cambodia.