A Phrase Set for Bengali/Bangla Text Entry Evaluations Based on Actual Text Messages

Ahmed Sabbir Arif & Sarah Fardeen


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Abstract — User studies evaluating text entry techniques usually require participants to transcribe phrases. Yet at present, there is no dataset available for Bengali text entry research that includes phrases entered on mobile devices. This forces researchers to collect phrases from various sources, compromising the external validity of the work. In this paper, we present a set of Bengali phrases composed by real users on actual mobile devices. Through an analysis of the dataset, we show that it contains phrases with varying lengths, symbols, and numbers.

For further details, see our paper below.

Ahmed Sabbir Arif and Sarah Fardeen. 2016. A phrase set for Bengali text entry evaluations based on actual text messages. In Proceedings of the 34th Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '16). ACM, New York, NY, USA, 2992-2998. DOI: http://dx.doi.org/10.1145/2851581.2892394

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See our paper on performance metrics for Bengali text entry research.

Sayan Sarcar, Ahmed Sabbir Arif, and Ali Mazalek. 2015. Metrics for Bengali text entry research. In CHI 2015 Workshop on Text Entry on the Edge (April 18, 2015). Seoul, South Korea, 4 pages.

Use WebTEM to record performance metrics for Bengali text entry techniques on any device.

Ahmed Sabbir Arif and Ali Mazalek. 2016. WebTEM: A Web application to record text entry metrics. In Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces (ISS '16). ACM, New York, NY, USA, 415-420. DOI: http://dx.doi.org/10.1145/2992154.2996791