Parallel texts corpora are essential resources especially in translation and multilingual information retrieval. However, the publicly available parallel text corpora are limited to certain types and domains. Besides, Malay dialects are not standardized in term of writing. The existing alignment algorithms that is used to analyze the writing will require a large training data to obtain a good result. The paper describes our methodology in acquiring a parallel text corpus of Standard Malay and Malay dialects, particularly Kelantan Malay and Sarawak Malay. Second, we propose a hybrid of distance-based and statistical-based alignment algorithm to align words and phrases of the parallel text. The proposed approach has a better precision and recall than the state-of-the-art GIZA++. In the paper, the alignment obtained were also compared to find out the lexical similarities and differences between SM and the two dialects.