Automatic extraction of bilingual Multi-Word Units is an important subject of research in the automatic bilingual corpus alignment field. There are many cases of single source words corresponding to target multi-word units. This paper presents an algorithm for the automatic alignment of single source words and target multi-word units from a sentence-aligned parallel spoken language corpus. On the other hand, the output can be also used to extract bilingual multi-word units. The problem with previous approaches is that the retrieval results mainly depend on the
identification of suitable Bi-grams to initiate the iterative process. To extract multi-word units, this algorithm utilizes the normalized association score difference of multi target words corresponding to the same single source word, and then utilizes the average association score to align the single source words and target multi-word units. The algorithm is based on the Local Bests algorithm supplemented by two heuristic strategies: excluding words in a stop-list and preferring longer multi-word units.