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HMS: A Predictive Text Entry Method using Bigrams

Hasselgren, Jon LU ; Montnemery, Erik; Svensson, Markus and Nugues, Pierre LU (2003) Workshop on Language Modeling for Text Entry Methods, 10th Conference of the European Chapter of the Association of Computational Linguistics In Proceedings of the Workshop on Language Modeling for Text Entry Methods p.43-49
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... (More)
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. (Less)
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in
Proceedings of the Workshop on Language Modeling for Text Entry Methods
pages
43 - 49
conference name
Workshop on Language Modeling for Text Entry Methods, 10th Conference of the European Chapter of the Association of Computational Linguistics
language
English
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yes
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07d733ff-baef-4b4a-ba37-9bc7a0b5f8d0 (old id 748311)
date added to LUP
2008-01-18 10:33:28
date last changed
2016-04-16 11:27:21
@inproceedings{07d733ff-baef-4b4a-ba37-9bc7a0b5f8d0,
  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<br/><br>
HMS, predicts words from a sequence of keystrokes using a dictionary and a function combining bigram frequencies<br/><br>
and word length.<br/><br>
<br/><br>
We implemented the HMS text entry method on a software-simulated mobile telephone keyboard and we compared it<br/><br>
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<br/><br>
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       = {Hasselgren, Jon and Montnemery, Erik and Svensson, Markus and Nugues, Pierre},
  booktitle    = {Proceedings of the Workshop on Language Modeling for Text Entry Methods},
  language     = {eng},
  pages        = {43--49},
  title        = {HMS: A Predictive Text Entry Method using Bigrams},
  year         = {2003},
}