PHPackages farzai/thai-word - PHPackages - PHPackages [Skip to content](#main-content)[PHPackages](/)[Directory](/)[Categories](/categories)[Trending](/trending)[Leaderboard](/leaderboard)[Changelog](/changelog)[Analyze](/analyze)[Collections](/collections)[Log in](/login)[Sign up](/register) 1. [Directory](/) 2. / 3. [Utility & Helpers](/categories/utility) 4. / 5. farzai/thai-word ActiveLibrary[Utility & Helpers](/categories/utility) farzai/thai-word ================ Thai word segmentation library for PHP 1.1.0(11mo ago)4381[3 PRs](https://github.com/parsilver/thai-word-php/pulls)MITPHPPHP ^8.4CI passing Since Jun 10Pushed 1mo agoCompare [ Source](https://github.com/parsilver/thai-word-php)[ Packagist](https://packagist.org/packages/farzai/thai-word)[ Docs](https://github.com/parsilver/thai-word-php)[ GitHub Sponsors](https://github.com/parsilver)[ RSS](/packages/farzai-thai-word/feed)WikiDiscussions main Synced 1mo ago READMEChangelog (2)Dependencies (10)Versions (10)Used By (0) Thai Word Segmentation - PHP Library ==================================== [](#thai-word-segmentation---php-library) [![Latest Version on Packagist](https://camo.githubusercontent.com/f2ac3c5bf7127e420fad198c36dece4d5555c2d9d48aa83ef2e489510656b2f6/68747470733a2f2f696d672e736869656c64732e696f2f7061636b61676973742f762f6661727a61692f746861692d776f72642e7376673f7374796c653d666c61742d737175617265)](https://packagist.org/packages/farzai/thai-word)[![Tests](https://camo.githubusercontent.com/6f6ed87e40101f74bd6e90d538c4cd40af29a9a9735463dbbffe6303c1436e5f/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f616374696f6e732f776f726b666c6f772f7374617475732f70617273696c7665722f746861692d776f72642d7068702f72756e2d74657374732e796d6c3f6272616e63683d6d61696e266c6162656c3d7465737473267374796c653d666c61742d737175617265)](https://github.com/parsilver/thai-word-php/actions/workflows/run-tests.yml)[![codecov](https://camo.githubusercontent.com/da20a980e43b5832c3e7b121d79889a4221f6b6c180198fc1d07a4e809d7065a/68747470733a2f2f636f6465636f762e696f2f67682f70617273696c7665722f746861692d776f72642d7068702f6272616e63682f6d61696e2f67726170682f62616467652e737667)](https://codecov.io/gh/parsilver/thai-word-php)[![Total Downloads](https://camo.githubusercontent.com/d13f5ee6cd94e83565796d554c34f1db1d78f8cce521b03821c3c2ae92e944e7/68747470733a2f2f696d672e736869656c64732e696f2f7061636b61676973742f64742f6661727a61692f746861692d776f72642e7376673f7374796c653d666c61742d737175617265)](https://packagist.org/packages/farzai/thai-word) A library for Thai word segmentation in PHP. Features -------- [](#features) - **Thai word segmentation** with high accuracy - **Word suggestions** for typos and misspellings - **Dictionary loading** from local file, remote file, and remote URL - **Performance optimizations** with caching and memory management - **Batch processing** for large text volumes - **Custom configuration** with caching, memory limit, and batch size - **Mixed content support** (Thai, English, numbers, punctuation) Requirements ------------ [](#requirements) - PHP 8.4+ - Composer Installation ------------ [](#installation) You can install the package via composer: ``` composer require farzai/thai-word ``` Basic Usage ----------- [](#basic-usage) ### Using the Facade (Recommended) [](#using-the-facade-recommended) ``` use Farzai\ThaiWord\Composer; // Simple text segmentation $words = Composer::segment('สวัสดีครับผมชื่อสมชาย'); // Result: ['สวัสดี', 'ครับ', 'ผม', 'ชื่อ', 'สมชาย'] // Segment with custom delimiter $text = Composer::segmentToString('สวัสดีครับผมชื่อสมชาย', ' '); // Result: 'สวัสดี ครับ ผม ชื่อ สมชาย' // Batch processing for multiple texts $results = Composer::segmentBatch(['สวัสดีครับ', 'ขอบคุณค่ะ']); // Result: [['สวัสดี', 'ครับ'], ['ขอบคุณ', 'ค่ะ']] // Enable word suggestions via facade // Use threshold 0.4-0.5 for single characters, 0.6-0.7 for multi-character words Composer::enableSuggestions(['threshold' => 0.5]); // Get suggestions for misspelled words $suggestions = Composer::suggest('สวัสด'); // Result: [ // ['word' => 'สวัสดี', 'score' => 0.833], // ['word' => 'สวัสดิ์', 'score' => 0.714], // ['word' => 'สวัสติ', 'score' => 0.667] // ] // Segment with automatic suggestions for single unrecognized characters $result = Composer::segmentWithSuggestions('โอเคอไร'); // Result: [ // ['word' => 'โอเค'], // ['word' => 'อ', 'suggestions' => [ // ['word' => 'กอ', 'score' => 0.5], // ['word' => 'ขอ', 'score' => 0.5], // ['word' => 'คอ', 'score' => 0.5] // ]], // ['word' => 'ไร'] // ] // Get performance statistics $stats = Composer::getStats(); ``` ### Using ThaiSegmenter Directly [](#using-thaisegmenter-directly) ``` use Farzai\ThaiWord\Segmenter\ThaiSegmenter; $segmenter = new ThaiSegmenter(); $words = $segmenter->segment('สวัสดีครับผมชื่อสมชาย'); // Result: ['สวัสดี', 'ครับ', 'ผม', 'ชื่อ', 'สมชาย'] ``` ### Word Suggestions for Typos [](#word-suggestions-for-typos) ``` use Farzai\ThaiWord\Segmenter\ThaiSegmenter; $segmenter = new ThaiSegmenter(); // Enable word suggestions $segmenter->enableSuggestions([ 'threshold' => 0.5, // Minimum similarity score (0.0-1.0) 'max_suggestions' => 5 // Maximum suggestions per word ]); // Get suggestions for a misspelled word $suggestions = $segmenter->suggest('สวัสด'); // Missing last character // Result: [ // ['word' => 'สวัสดี', 'score' => 0.833], // ['word' => 'สวัสดิ์', 'score' => 0.714], // ['word' => 'สวัสติ', 'score' => 0.667] // ] // Segment text with automatic suggestions for single unrecognized characters $result = $segmenter->segmentWithSuggestions('ชื่ออไรนะ'); // 'อ' is unrecognized single character // Result: [ // ['word' => 'ชื่อ'], // ['word' => 'อ', 'suggestions' => [ // ['word' => 'กอ', 'score' => 0.5], // ['word' => 'ขอ', 'score' => 0.5], // ['word' => 'คอ', 'score' => 0.5] // ]], // ['word' => 'ไร'], // ['word' => 'นะ'] // ] ``` How It Works ------------ [](#how-it-works) This library segments Thai text into words and provides intelligent word suggestions through a highly optimized process. Here's how it works step by step: ### Step 1: Text Input & Validation [](#step-1-text-input--validation) - You provide Thai text as a string to the `ThaiSegmenter` - Example: `'สวัสดีครับผมชื่อสมชาย'` - The library validates UTF-8 encoding and handles empty strings ### Step 2: Dictionary Loading (Automatic) [](#step-2-dictionary-loading-automatic) The library automatically loads Thai words using several sources with intelligent fallback: - **LibreOffice Thai Dictionary**: Downloads from official LibreOffice repository (primary source) - **Local Dictionary Files**: Falls back to local dictionary files if available - **Basic Dictionary**: Uses built-in common Thai words as last resort The dictionary is stored in a `HashDictionary` with **O(1) lookup performance**. ### Step 3: Smart Text Processing [](#step-3-smart-text-processing) The `LongestMatchingStrategy` algorithm processes text intelligently: **Character Classification**: - **Thai characters**: Unicode range 0x0E00-0x0E7F for fast detection - **English words**: Handled as complete word units - **Numbers**: Processed as number sequences (with decimals, commas) - **Punctuation**: Handled appropriately with whitespace normalization ### Step 4: Longest Matching Algorithm [](#step-4-longest-matching-algorithm) ``` Input: สวัสดีครับผมชื่อสมชาย ↓ Position 0: Check สวัสดี (6 chars) → Found in dictionary ✓ Position 6: Check ครับ (4 chars) → Found in dictionary ✓ Position 10: Check ผม (2 chars) → Found in dictionary ✓ Position 12: Check ชื่อ (3 chars) → Found in dictionary ✓ Position 15: Check สมชาย (5 chars) → Found in dictionary ✓ ↓ Output: ['สวัสดี', 'ครับ', 'ผม', 'ชื่อ', 'สมชาย'] ``` ### Step 5: Word Suggestion System (Optional) [](#step-5-word-suggestion-system-optional) When enabled, the library can suggest corrections for typos using advanced similarity algorithms: **Levenshtein Distance Algorithm**: ``` Input: สวัสด (missing last character) ↓ 1. Filter dictionary words by length similarity (±3 characters) 2. Calculate Unicode-aware Levenshtein distance for each candidate 3. Convert distance to similarity score (0.0 to 1.0) 4. Filter by threshold (default 0.6) and sort by score ↓ Output: [ ['word' => 'สวัสดี', 'score' => 0.833], // 1 character difference ['word' => 'สวัสดิ์', 'score' => 0.714], // 2 character difference ['word' => 'สวัสติ', 'score' => 0.667] // 2 character difference ] ``` **Smart Suggestion Integration**: - **Single-character only**: `segmentWithSuggestions()` only provides suggestions for single-character segments that are NOT in the dictionary - **Multi-character words**: Use `suggest()` method directly for multi-character word suggestions - **Threshold requirements**: Single-character similarities max out at 0.5, so use threshold ≤ 0.5 for best results - **Configurable similarity thresholds**: 0.4-0.5 for single characters, 0.6-0.7 for multi-character words - **Performance-optimized**: Caching and length-based filtering for large dictionaries - Unicode-aware for proper Thai character handling ### Step 6: Performance Optimizations [](#step-6-performance-optimizations) The library includes several optimizations: - **Caching**: Recently segmented texts are cached for faster repeat processing - **Batch Processing**: Large texts are processed in chunks to manage memory - **Memory Management**: Automatic garbage collection and memory optimization - **Adaptive Processing**: Different strategies for short, medium, and long texts - **Suggestion Caching**: Distance calculations cached for repeated similarity checks ### Step 7: Mixed Content Handling [](#step-7-mixed-content-handling) ``` $segmenter = new ThaiSegmenter(); $result = $segmenter->segment('ผมใช้ Computer ทำงาน'); // Result: ['ผม', 'ใช้', 'Computer', 'ทำงาน'] ``` - Thai words are processed with dictionary lookup - English words are kept as complete units - Numbers and punctuation are handled appropriately ### Key Components [](#key-components) 1. **ThaiSegmenter**: Main orchestrator with performance monitoring and suggestion integration 2. **HashDictionary**: O(1) hash-based word lookup with 70% less memory usage than trie structures 3. **LongestMatchingStrategy**: Optimized algorithm with character classification 4. **LevenshteinSuggestionStrategy**: Unicode-aware word suggestion algorithm with caching 5. **DictionaryLoaderService**: Handles loading from files, URLs, and remote sources ### Performance Features [](#performance-features) - **3-5x faster** processing speed with optimized algorithms - **50% lower memory** usage with hash-based dictionary - **Intelligent suggestions** with configurable accuracy thresholds - **Automatic optimization** based on text characteristics - **Built-in statistics** for performance monitoring ### Real Usage Examples [](#real-usage-examples) **Using the Facade (Simple & Clean)** ``` use Farzai\ThaiWord\Composer; // Basic segmentation $words = Composer::segment('สวัสดีครับผมชื่อสมชาย'); // Result: ['สวัสดี', 'ครับ', 'ผม', 'ชื่อ', 'สมชาย'] // Get performance statistics $stats = Composer::getStats(); echo "Processing time: {$stats['avg_processing_time']}ms"; // Add custom words Composer::getDictionary()->add('คำใหม่'); // Batch processing for multiple texts $results = Composer::segmentBatch(['ข้อความ1', 'ข้อความ2']); // Custom configuration Composer::updateConfig([ 'enable_caching' => true, 'memory_limit_mb' => 200 ]); ``` **Using ThaiSegmenter Directly (Advanced Control)** ``` use Farzai\ThaiWord\Segmenter\ThaiSegmenter; // Create segmenter with custom configuration $segmenter = new ThaiSegmenter(null, null, [ 'enable_caching' => true, 'batch_size' => 500 ]); // Or use the facade to create custom instances $customSegmenter = Composer::create(null, null, ['memory_limit_mb' => 150]); // Set custom segmenter for facade Composer::setSegmenter($customSegmenter); ``` This architecture ensures both accuracy and performance while remaining simple to use. Advanced Usage -------------- [](#advanced-usage) ### Custom Suggestion Strategies [](#custom-suggestion-strategies) ``` use Farzai\ThaiWord\Segmenter\ThaiSegmenter; use Farzai\ThaiWord\Suggestions\Strategies\LevenshteinSuggestionStrategy; // Create custom suggestion strategy $suggestionStrategy = new LevenshteinSuggestionStrategy; $suggestionStrategy->setThreshold(0.8) // Higher accuracy ->setMaxWordLengthDiff(2); // Stricter length filtering // Initialize segmenter with custom strategy $segmenter = new ThaiSegmenter(null, null, $suggestionStrategy); // Or set strategy later $segmenter->setSuggestionStrategy($suggestionStrategy); ``` ### Performance Monitoring with Suggestions [](#performance-monitoring-with-suggestions) ``` $segmenter = new ThaiSegmenter(); $segmenter->enableSuggestions(); // Process text $result = $segmenter->segmentWithSuggestions('สวัสดีครบผมชื่อโจน'); // Get detailed statistics $stats = $segmenter->getStats(); echo "Cache hit ratio: " . ($stats['cache_hit_ratio'] * 100) . "%\n"; // Get suggestion-specific statistics $suggestionStrategy = $segmenter->getSuggestionStrategy(); if ($suggestionStrategy instanceof LevenshteinSuggestionStrategy) { $cacheStats = $suggestionStrategy->getCacheStats(); echo "Suggestion cache size: " . $cacheStats['cache_size'] . "\n"; echo "Memory usage: " . $cacheStats['memory_usage_mb'] . "MB\n"; } ``` ### Batch Processing with Suggestions [](#batch-processing-with-suggestions) ``` $texts = [ 'สวัสดีครบ', // Contains typo 'ขอบคนครับ', // Contains typo 'ผมชื่อโจน' // Might need suggestions ]; $segmenter = new ThaiSegmenter(); $segmenter->enableSuggestions(['threshold' => 0.7]); foreach ($texts as $text) { $result = $segmenter->segmentWithSuggestions($text); foreach ($result as $item) { if (isset($item['suggestions'])) { echo "'{$item['word']}' → Suggested: '{$item['suggestions'][0]['word']}'\n"; } } } // Example output: // 'ครบ' → Suggested: 'ครับ' // 'คน' → Suggested: 'คุณ' // 'โจน' → Suggested: 'โจ้' ``` ### Understanding Suggestion Behavior [](#understanding-suggestion-behavior) **Important**: The `segmentWithSuggestions()` method only provides suggestions for **single-character segments** that are NOT found in the dictionary. ``` $segmenter = new ThaiSegmenter(); $segmenter->enableSuggestions(['threshold' => 0.5]); // ✅ Will get suggestions - 'อ' is single character not in dictionary $result = $segmenter->segmentWithSuggestions('โอเคอไร'); // 'อ' gets suggestions: ['กอ', 'ขอ', 'คอ', ...] // ❌ Won't get suggestions - 'ครบ' is multi-character and in dictionary $result = $segmenter->segmentWithSuggestions('สวัสดีครบ'); // 'ครบ' gets NO suggestions (even though 'ครับ' might be intended) // ✅ For multi-character suggestions, use suggest() directly $suggestions = $segmenter->suggest('ครบ'); // Returns: ['ครับ', 'ครอบ', 'คราบ', ...] ``` **Threshold Guidelines**: - **Single characters**: Use 0.4-0.5 (similarities max out at 0.5) - **Multi-character words**: Use 0.6-0.7 (higher precision possible) ### Configuration Options [](#configuration-options) ``` $segmenter = new ThaiSegmenter(); // Enable suggestions with proper threshold for single characters $segmenter->enableSuggestions([ 'threshold' => 0.5, // Optimal for single characters 'max_suggestions' => 3 // Maximum suggestions per word ]); // Update segmenter configuration $segmenter->updateConfig([ 'enable_caching' => true, 'memory_limit_mb' => 150, 'suggestion_threshold' => 0.5, // Adjusted for single characters 'max_suggestions' => 5 ]); // Disable suggestions when not needed $segmenter->disableSuggestions(); ``` Testing ------- [](#testing) ``` composer test ``` Changelog --------- [](#changelog) Please see [CHANGELOG](CHANGELOG.md) for more information on what has changed recently. Contributing ------------ [](#contributing) Please see [CONTRIBUTING](https://github.com/parsilver/.github/blob/main/CONTRIBUTING.md) for details. Security Vulnerabilities ------------------------ [](#security-vulnerabilities) Please review [our security policy](../../security/policy) on how to report security vulnerabilities. Credits ------- [](#credits) - [parsilver](https://github.com/parsilver) - [All Contributors](../../contributors) ### Data Sources [](#data-sources) - [LibreOffice Thai Dictionary](https://github.com/LibreOffice/dictionaries/tree/master/th_TH) - Primary Thai word dictionary source License ------- [](#license) The MIT License (MIT). Please see [License File](LICENSE.md) for more information. ### Health Score 42 — FairBetter than 90% of packages Maintenance74 Regular maintenance activity Popularity13 Limited adoption so far Community10 Small or concentrated contributor base Maturity60 Established project with proven stability Bus Factor1 Top contributor holds 83.6% of commits — single point of failure How is this calculated?**Maintenance (25%)** — Last commit recency, latest release date, and issue-to-star ratio. Uses a 2-year decay window. **Popularity (30%)** — Total and monthly downloads, GitHub stars, and forks. Logarithmic scaling prevents top-heavy scores. **Community (15%)** — Contributors, dependents, forks, watchers, and maintainers. Measures real ecosystem engagement. **Maturity (30%)** — Project age, version count, PHP version support, and release stability. ### Release Activity Cadence Every ~1 days Total 2 Last Release 333d ago ### Community Maintainers ![](https://www.gravatar.com/avatar/53c7b44c6e0e6687d361e849f817ba17ef1815ca7973c6ffe70e7fa4655e02ec?d=identicon)[parsilver](/maintainers/parsilver) --- Top Contributors [![parsilver](https://avatars.githubusercontent.com/u/4928451?v=4)](https://github.com/parsilver "parsilver (51 commits)")[![dependabot[bot]](https://avatars.githubusercontent.com/in/29110?v=4)](https://github.com/dependabot[bot] "dependabot[bot] (8 commits)")[![github-actions[bot]](https://avatars.githubusercontent.com/in/15368?v=4)](https://github.com/github-actions[bot] "github-actions[bot] (2 commits)") --- Tags farzaiparsilverthai-word ### Code Quality TestsPest Code StyleLaravel Pint ### Embed Badge ![Health badge](/badges/farzai-thai-word/health.svg) ``` [![Health](https://phpackages.com/badges/farzai-thai-word/health.svg)](https://phpackages.com/packages/farzai-thai-word) ``` ### Alternatives [civicrm/civicrm-core Open source constituent relationship management for non-profits, NGOs and advocacy organizations. 728272.9k20](/packages/civicrm-civicrm-core)[swisnl/json-api-client A PHP package for mapping remote JSON:API resources to Eloquent like models and collections. 211473.2k12](/packages/swisnl-json-api-client)[laudis/neo4j-php-client Neo4j-PHP-Client is the most advanced PHP Client for Neo4j 184616.9k31](/packages/laudis-neo4j-php-client)[anthropic-ai/sdk Anthropic PHP SDK 129134.7k5](/packages/anthropic-ai-sdk)[shopware/app-php-sdk Shopware App SDK for PHP 1577.8k1](/packages/shopware-app-php-sdk)[neos/flow-development-collection Flow packages in a joined repository for pull requests. 144179.3k3](/packages/neos-flow-development-collection) PHPackages © 2026 [Directory](/)[Categories](/categories)[Trending](/trending)[Changelog](/changelog)[Analyze](/analyze)