Speech-based Cursor Control

Azfar S. Karimullah and Andrew Sears


Interactive Systems Research Center, UMBC, Baltimore, USA


Speech recognition can be a powerful tool for individuals with physical disabilities that hinder their ability to use traditional input devices. State-of-the-art speech recognition systems typically provide mechanisms for both data entry and cursor control, but the researchers continue to investigate methods of improving these interactions. Numerous researchers are investigating methods to improve the underlying technologies that make speech recognition possible and others focus on understanding the difficulties users experience using dictation-oriented applications, but few researchers have investigated the issues involved in speech-based cursor control. In this article, we describe a study that investigates the efficacy of two variations of a standard speech-based cursor control mechanism. One employs the standard mouse cursor while the second provides a predictive cursor designed to help users compensate for the delays often associated with speech recognition. As expected, larger targets and shorter distances resulted in shorter target selection times while larger targets also resulted in fewer errors. Although there were no differences between the standard and predictive cursors, a relationship between the delays associated with spoken input, the speed at which the cursor moves, and the minimum size for targets that can be reliably selected emerged that can guide the application of similar speech-based cursor control mechanisms as well as future research.

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