Gorman, Benjamin Millar
At least 360 million people worldwide have disabling hearing loss that frequently causes difficulties in day-to-day conversations. Hearing aids often fail to offer enough benefits and have low adoption rates. However, people with hearing loss find that speechreading can improve their understanding during conversation. Speechreading (often called lipreading) refers to using visual information about the movements of a speaker’s lips, teeth, and tongue to help understand what they are saying. Speechreading is commonly used by people with all severities of hearing loss to understand speech, and people with typical hearing also speechread (albeit subconsciously) to help them understand others.
However, speechreading is a skill that takes considerable practice to acquire. Publicly-funded speechreading classes are sometimes provided, and have been shown to improve speechreading acquisition. However, classes are only provided in a handful of countries around the world and students can only practice effectively when attending class. Existing tools have been designed to help improve speechreading acquisition, but are often not effective because they have not been designed within the context of contemporary speechreading lessons or practice.
To address this, in this thesis I present a novel speechreading acquisition framework that can be used to design Speechreading Acquisition Tools (SATs) – a new type of technology to improve speechreading acquisition. I interviewed seven speechreading tutors and used thematic analysis to identify and organise the key elements of the framework. I evaluated the framework by using it to: 1) categorise every tutor-identified speechreading teaching technique, 2) critically evaluate existing Conversation Aids and SATs, and 3) design three new SATs.
I then conducted a postal survey with 59 speechreading students to understand students’ perspectives on speechreading, and how their thoughts could influence future SATs. To further evaluate the framework’s effectiveness I then developed and evaluated two new SATs (PhonemeViz and MirrorMirror) designed using the framework. The findings from the evaluation of these two new SATs demonstrates that using the framework can help design effective tools to improve speechreading acquisition.