Abstract In this paper, we study Braille word segmentation and transformation of Mandarin Braille to Chinese characters. The former consists of rule, sign and knowledge bases for disambiguation and mistake correction by using adjacent constraints and bi-directional maximal matching in which segmentation precision is better than 99%. The latter can be divided into two stages: Braille to Chinese pinyin (a phonemic Romanization) and pinyin to characters. By incorporating a pinyin knowledge dictionary into the system, we have perfectly solved the problem of ambiguity in the translation from Braille to pinyin and developed a statistical language model based on the transformation of pinyin to characters. By using Viterbi search, we have built a multi-level graph and found the sequence of Chinese characters with maximal likelihood. By using an N-Best algorithm to get the N most likely character sequences and probing into the means of measurement, our correct candidates within the top-five have a further improvement of 3%. By testing on 40,000 Chinese characters for the evaluation of the system performance, our overall translation precision of Braille codes to Chinese characters for common documents arrives at 94.38%; if proper nouns are not considered, our improvement reaches 2%.