HMM-Based Probabilistic Flick Keyboard Adaptable to Individual User

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To provide an accurate and user-adaptable software keyboard for touchscreens, we propose a probabilistic flick keyboard based on hidden Markov models (HMMs). Touch and flick operations for each character are modeled by HMMs. This keyboard reduces input errors by taking the trajectory of the actual touch position into consideration and by user adaptation. We evaluated the performance of an HMM-based flick keyboard and maximum-likelihood linear regression (MLLR) adaptation. Experimental results showed that a user-dependent model reduced the error rate by 28.3%. In a practical setting, the MLLR adaptation to a specific user with only 10 words reduced the error rate by 16.6% and increased the typing speed by 11.9%.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.22(2014) No.2 (online)DOI http://dx.doi.org/10.2197/ipsjjip.22.410------------------------------

To provide an accurate and user-adaptable software keyboard for touchscreens, we propose a probabilistic flick keyboard based on hidden Markov models (HMMs). Touch and flick operations for each character are modeled by HMMs. This keyboard reduces input errors by taking the trajectory of the actual touch position into consideration and by user adaptation. We evaluated the performance of an HMM-based flick keyboard and maximum-likelihood linear regression (MLLR) adaptation. Experimental results showed that a user-dependent model reduced the error rate by 28.3%. In a practical setting, the MLLR adaptation to a specific user with only 10 words reduced the error rate by 16.6% and increased the typing speed by 11.9%.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.22(2014) No.2 (online)DOI http://dx.doi.org/10.2197/ipsjjip.22.410------------------------------

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詳細情報 詳細情報について

  • CRID
    1050845762834573440
  • NII論文ID
    110009752411
  • NII書誌ID
    AN00116647
  • ISSN
    18827764
  • Web Site
    http://id.nii.ac.jp/1001/00099474/
  • 本文言語コード
    en
  • 資料種別
    journal article
  • データソース種別
    • IRDB
    • CiNii Articles

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