If the objective of a continuous automatic speech understanding system is not a speech-to-text translation, words are not strictly needed, and then the use of alternative lexical units (LUs) will bring us a new degree of freedom to improve the system performance. Consequently, we experimentally explore some methods to automatically extract a set of LUs from a Spanish training corpus and verify that the system can be improved in two ways: reducing the computational costs and increasing the recognition rates. Moreover, preliminary results point out that, even if the system target is a speech-to-text translation, using non-word units and post-processing the output to produce the corresponding word chain outperforms the word based system