HMS: a predictive text entry method using bigrams

Authors:
Jon Hasselgren;Erik Montnemery;Pierre Nugues;Markus Svensson
Affiliations:
Lund Institute of Technology, Lund, Sweden;Lund Institute of Technology, Lund, Sweden;Lund Institute of Technology, Lund, Sweden;Lund Institute of Technology, Lund, Sweden
Venue:
TextEntry '03 Proceedings of the 2003 EACL Workshop on Language Modeling for Text Entry Methods
Year:
2003

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Abstract

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.