A New Approach To Accent Restoration Of Vietnamese Texts Using Dynamic Programming Combined With Co-Occurrence Graph

摘要

In this paper, we would like to introduce a new approach to recover Vietnamese text's accents. Given a Vietnamese text in which accents are lost, our goal is to seek for a recovered text that yields a best lexical probability. Using a dynamic programming approach, we first build a model of language for Vietnamese as a lexical database which gives lexical probabilities to Vietnamese sentences. Second, we construct a map of literal translations of Vietnamese words to restrict our searching space. Finally, we apply dynamic programming as a searching engine to seek out the most probable sentence. We also use the co-occurrence graph to increase the accuracy of selection, the experimental results show that the average accuracy of our approach is about 93%-94%.