中國大陸與台灣的文字同屬於華文字體，但字體上卻分為簡體字與繁體字。中國大陸與台灣近年來在中文書籍及網路上皆有大量的資訊交流。基於閱讀習慣，文字勢必需要執行簡繁轉換後才利於雙方的讀者閱讀。傳統的簡繁轉換擁有簡體一字對繁體多字的歧異問題以及兩岸用語不同的問題。因此，本研究設計一個具有擴展性的簡繁轉換系統，透過人工擷取維基百科新增對照表內容來改善兩岸用語不同的問題，以及使用語言模型改善簡體字一個字對繁體字多個字的歧異問題。此系統可以降低各種中文電子書籍執行簡繁轉換後人工校正的成本。具有彈性的架構使得系統可以持續擴充改進。

The character sets used in China and Taiwan are both Chinese, but they are divided into simplified and traditional Chinese characters. There are large amount of information exchange between China and Taiwan through books and Internet. To provide readers a convenient reading environment, the character conversion between simplified and traditional Chinese is necessary. The conversion between simplified and traditional Chinese characters has two problems: one-to-many ambiguity and term usage problems. Since there are many traditional Chinese characters that have only one corresponding simplified character, when converting simplified Chinese into traditional Chinese, the system will face the one-to-many
ambiguity. Also, there are many terms that have different usages between the two Chinese societies. This paper focus on designing an extensible conversion system, that can take the advantage of community knowledge by accumulating lookup tables through Wikipedia to tackle the term usage problem and can integrate language model to disambiguate the one-to-many ambiguity. The system can reduce the cost of proofreading of character conversion for books, e-books, or online publications. The extensible architecture makes it easy to improve the system with new training data.