Abstract
A number of text entry methods use a predictive completion based on letter-level n-gram model. In this paper, we investigate on an optimal length of n-grams stored in such model for a predictive keyboard operated by humming. In order to find the length, we analyze six different corpora, from which a model is built by counting number of primitive operations needed to enter a text. Based on these operations, we provide a formula for estimation of words per minute (WPM) rate. The model and the analysis results are verified in an experiment with three experienced users of the keyboard.
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Poláček, O., Sporka, A.J., Míkovec, Z. (2012). Measuring Performance of a Predictive Keyboard Operated by Humming. In: Miesenberger, K., Karshmer, A., Penaz, P., Zagler, W. (eds) Computers Helping People with Special Needs. ICCHP 2012. Lecture Notes in Computer Science, vol 7383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31534-3_69
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DOI: https://doi.org/10.1007/978-3-642-31534-3_69
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