The Universal Word Frequency Counter & N-Gram Lexical Density Studio is an advanced, privacy-first lexical analytics utility tailored for content writers, SEO specialists, editors, and academic researchers. Operating 100% inside your browser session using high-performance client-side NLP tokenization, the studio scans texts, speeches, and manuscripts without transmitting a single byte to an external server. It accurately tallies word occurrences, computes real-time keyword density percentages, extracts 1-Gram (unigrams), 2-Gram (bigrams), and 3-Gram (trigrams) phrase sequences, and calculates the Type-Token Ratio (TTR) to assess vocabulary richness and lexical diversity. Featuring customizable stop-word filtering, case-sensitivity toggles, digit exclusions, syllable and readability estimators (reading & speaking pace calibration), an interactive visual keyword cloud, and 1-click export to CSV, JSON, and TXT, this studio is the definitive tool to eliminate keyword stuffing and optimize digital content for modern semantic search.

RiazHub Digital NLP Suite

Universal Word Frequency Counter

Analyze keyword density, track 1/2/3-word phrase occurrences, calculate lexical diversity, and inspect vocabulary distribution in real time.

Quick Preset Profiles

Total Words

0 characters

Unique Vocabulary

0.0% Lexical Diversity (TTR)

Reading Time

0.0 min

0.0 min speaking @ 130 WPM

Top Keyword

—

0 occurrences (0.0%)

Source Text

0 words

Characters: 0 | Words: 0 Paragraphs: 0

Drop document or click to upload (.txt, .md, .csv)

Analysis Scope & Filters

N-Gram Phrase Mode

Filter Stop Words Prune common fillers (the, a, and, of, in...)

Case Sensitive Matching Distinguish "Apple" from "apple"

Ignore Numbers & Digits Exclude standalone numerals from tally

Minimum Character Length

Minimum Occurrences (Appear ≥ N)

Custom Excluded Words (Comma-separated)

#	Keyword / Phrase	Count	Density
Paste text in the left panel to generate keyword frequency matrix

Interactive tag cloud will render here automatically

Character & Word Metrics

Total Characters (With spaces) 0
Characters (Without spaces) 0
Total Words 0
Unique Vocabulary 0
Average Word Length 0.0 chars

Structure & Readability Pace

Total Sentences 0
Total Paragraphs 0
Estimated Syllables 0
Average Sentence Length 0.0 words
Silent Reading Time (225 WPM) 0.0 min
Spoken Presentation Time (130 WPM) 0.0 min

Lexical Density, SEO Keyword Stuffing & NLP Text Metrics Guide

Modern search engines (like Google, Bing, and search AI crawlers) emphasize natural language processing (NLP) and topical relevance over keyword repetition. For primary focus keywords, an optimal keyword density usually ranges between 1.0% and 2.5%. Exceeding 3% to 4% risks triggering algorithmic over-optimization or keyword-stuffing penalties, whereas falling below 0.5% may fail to establish topical authority.

Type-Token Ratio (TTR) is calculated by dividing the number of unique word types by the total number of word tokens ($TTR = \frac{\text{Unique Words}}{\text{Total Words}} \times 100\%$). A high TTR (45%–65%+) signifies rich vocabulary diversity and sophisticated linguistic style, typical of academic papers and literature. A lower TTR (below 30%) indicates repetitive language or highly specialized technical jargon.

While single words (unigrams) capture general vocabulary, multi-word phrases (bigrams such as "digital marketing" and trigrams such as "search engine optimization") represent cohesive named entities. Analyzing bigrams and trigrams allows content creators to align with exact user search intents and semantic knowledge graphs.

All tokenization, regex splitting, frequency map aggregation, stop-word filtering, and metric calculations run 100% inside your browser session via client-side JavaScript. No articles, confidential manuscripts, legal briefs, or SEO drafts are ever uploaded, saved, or transmitted to any external server.

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