Open Access Te Herenga Waka-Victoria University of Wellington
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Investigating the effects of corpus and configuration on assistive input methods

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posted on 2021-11-14, 11:03 authored by Hindmarsh, Samuel

Assistive technologies aim to provide assistance to those who are unable to perform various tasks in their day-to-day lives without tremendous difficulty. This includes — amongst other things — communicating with others. Augmentative and adaptive communication (AAC) is a branch of assistive technologies which aims to make communicating easier for people with disabilities which would otherwise prevent them from communicating efficiently (or, in some cases, at all). The input rate of these communication aids, however, is often constrained by the limited number of inputs found on the devices and the speed at which the user can toggle these inputs. A similar restriction is also often found on smaller devices such as mobile phones: these devices also often require the user to input text with a smaller input set, which often results in slower typing speeds.  Several technologies exist with the purpose of improving the text input rates of these devices. These technologies include ambiguous keyboards, which allow users to input text using a single keypress for each character and trying to predict the desired word; word prediction systems, which attempt to predict the word the user is attempting to input before he or she has completed it; and word auto-completion systems, which complete the entry of predicted words before all the corresponding inputs have been pressed.  This thesis discusses the design and implementation of a system incorporating the three aforementioned assistive input methods, and presents several questions regarding the nature of these technologies. The designed system is found to outperform a standard computer keyboard in many situations, which is a vast improvement over many other AAC technologies. A set of experiments was designed and performed to answer the proposed questions, and the results of the experiments determine that the corpus used to train the system — along with other tuning parameters — have a great impact on the performance of the system. Finally, the thesis also discusses the impact that corpus size has on the memory usage and response time of the system.


Copyright Date


Date of Award



Te Herenga Waka—Victoria University of Wellington

Rights License

Author Retains Copyright

Degree Discipline

Software Engineering

Degree Grantor

Te Herenga Waka—Victoria University of Wellington

Degree Level


Degree Name

Master of Engineering

ANZSRC Type Of Activity code

970108 Expanding Knowledhe in the Information and Computing Sciences

Victoria University of Wellington Item Type

Awarded Research Masters Thesis



Victoria University of Wellington School

School of Engineering and Computer Science


Marshall, Stuart; Zhang, Mengjie