Abstract: A pioneering step in designing Bi-gram based decoder for SMS Lingo SMS Lingo is a language used by young generation for instant messaging for chatting on social networking websites called chatting slang. Such terms often originate with the purpose of saving keystrokes. In last few decades, a significant increment in both the computational power and storage capacity of computers have made possible for Statistical Machine Translation (SMT) to become a concrete and realistic tool. But still it demands for larger storage capacity. My past research employs Bi-gram Back-off Language Model (LM) with a SMT decoder through which a sentence written with short forms in an SMS is translated into long form sentence using non-multiplexed Probability Distribution Tables (PDT). Here, in this study the same is proposed using multiplexed PDT (a single PDT) for Uni-gram and Bi-gram, so smaller memory requirements. Use of N-gram LM in chatting slang with multiplexed PDT is the objective behind this work. As this application is meant for small devices like mobile phones, researchers can prove this approach a memory saver.