HMS: A Predictive Text Entry Method using Bigrams

Summary, in English

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.

• Author: Jon Hasselgren; Erik Montnemery; Markus Svensson; Pierre Nugues
• Department/s: Department of Computer Science; Robotics and Semantic Systems
• Publishing year: 2003
• Language: English
• Pages: 43-49
• Publication/Series: Proceedings of the Workshop on Language Modeling for Text Entry Methods
• Full text: - 89 kB; Download statistics
• Document type: Conference paper
• Topic: Computer Science
• Conference name: Workshop on Language Modeling for Text Entry Methods, 10th Conference of the European Chapter of the Association of Computational Linguistics
• Conference date: 2003-04-14
• Status: Published