HMS: A Predictive Text Entry Method using Bigrams

Due to the emergence of SMS messages, the significance of effective text entry on limited-size keyboards has increased. In this paper, we describe and discuss a new method to enter text more efficiently using a mobile telephone keyboard. This method, which we called HMS, predicts words from a sequence of keystrokes using a dictionary and a function combining bigram frequencies and word length. We implemented the HMS text entry method on a software-simulated mobile telephone keyboard and we compared it to a widely available commercial system. We trained the language model on a corpus of Swedish news and we evaluated the method. Although the training corpus does not reflect the language used in SMS messages, the results show a decrease by 7 to 13 percent in the number of keystrokes needed to enter a text. These figures are very encouraging even though the implementation can be optimized in several ways. The HMS text entry method can easily be transferred to other languages