Implementing a hands-free workstation : detailing the setup and configuration of accessibility tools combined with operating system enhancements
Farhadi, Amir (2024)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024120231895
https://urn.fi/URN:NBN:fi:amk-2024120231895
Tiivistelmä
Popular speech accessibility software like Dragon, Windows Speech Recognition, or Voice Access in Windows 11 offer accurate text transcription and basic functionality for tasks like web searches and document creation. However, these tools fall short in providing efficient control over application UI elements, editing text, or switching applications due to their lack of customizable speech grammars, forcing users to work within predefined constraints.
This thesis presents the implementation of a hands-free workstation for Windows 10 using open-source software. The implementation utilizes Caster, a Dragonfly-based accessibility tool, with Kaldi Active Grammar as the speech recognition engine. For mouse cursor control, Enable Viacam is employed, while Hunt and Peck enhances UI interaction. Additional software like WindHawk and 7+ Taskbar Numberer improves application switching.
When used together, the software suite enables efficient hands-free control of the computer, significantly improving accessibility for users who are unable to use a keyboard and mouse with their arms.
This thesis presents the implementation of a hands-free workstation for Windows 10 using open-source software. The implementation utilizes Caster, a Dragonfly-based accessibility tool, with Kaldi Active Grammar as the speech recognition engine. For mouse cursor control, Enable Viacam is employed, while Hunt and Peck enhances UI interaction. Additional software like WindHawk and 7+ Taskbar Numberer improves application switching.
When used together, the software suite enables efficient hands-free control of the computer, significantly improving accessibility for users who are unable to use a keyboard and mouse with their arms.