Keywords
Modern applications provide interfaces for scripting, but many users do not know how to write script commands. However, many users are familiar with the idea of entering keywords into a web search engine. Hence, if a user is familiar with the vocabulary of an application domain, we anticipate that they could write a set of keywords expressing a command in that domain. For instance, in the web browsing domain, a user might enter <B>click search button</B>. We call expressions of this form keyword commands, and we present a novel approach for translating keyword commands directly into executable code. Our prototype of this system in the web browsing domain translates <B>click search button</B> into the Chickenfoot code <B>click(findButton("search"))</B>. This code is then executed in the context of a web browser to carry out the effect. We also present an implementation of this system in the domain of Microsoft Word. A user study revealed that subjects could use keyword commands to successfully complete 90% of the web browsing tasks in our study without instructions or training. Conversely, we would expect users to complete close to 0% of the tasks if they had to guess the underlying JavaScript commands with no instructions or training.
This paper presents a new GUI architecture for creating advanced interfaces. This model is based on a limited set of general principles that improve flexibility and provide capabilities for implementing information visualization techniques such as magic lenses, transparent tools or semantic zooming. This architecture also makes it possible to create multiple views and application-sharing systems (by sharing views on multiple computer screens) in a simple and uniform way and to handle bimanual interaction and multiple pointers. An experimental toolkit called Ubit was implemented to test the feasibility of this approach. It is based on a pseudo-declarative C++ API that tries to simplify GUI programming by providing a higher level of abstraction.
A new technique to enter text using a mobile phone keypad is described. For text input, the traditional touchtone phone keypad is ambiguous because each key encodes three or four letters. Instead of using a stored dictionary to guess the intended word, our technique uses probabilities of letter sequences --- "prefixes" --- to guess the intended letter. Compared to dictionary-based methods, this technique, called LetterWise, takes significantly less memory and allows entry of non-dictionary words without switching to a special input mode. We conducted a longitudinal study to compare LetterWise to Multitap, the conventional text entry method for mobile phones. The experiment included 20 participants (10 LetterWise, 10 Multitap), and each entered phrases of text for 20 sessions of about 30 minutes each. Error rates were similar between the techniques; however, by the end of the experiment the mean entry speed was 36% faster with LetterWise than with Multitap.
Modern applications provide interfaces for scripting, but many users do not know how to write script commands. However, many users are familiar with the idea of entering keywords into a web search engine. Hence, if a user is familiar with the vocabulary of an application domain, we anticipate that they could write a set of keywords expressing a command in that domain. For instance, in the web browsing domain, a user might enter <B>click search button</B>. We call expressions of this form keyword commands, and we present a novel approach for translating keyword commands directly into executable code. Our prototype of this system in the web browsing domain translates <B>click search button</B> into the Chickenfoot code <B>click(findButton("search"))</B>. This code is then executed in the context of a web browser to carry out the effect. We also present an implementation of this system in the domain of Microsoft Word. A user study revealed that subjects could use keyword commands to successfully complete 90% of the web browsing tasks in our study without instructions or training. Conversely, we would expect users to complete close to 0% of the tasks if they had to guess the underlying JavaScript commands with no instructions or training.
Spoken language interfaces provide highly mobile, small form-factor, hands-free, eyes-free interaction with information. Uniform access to large lists of information using spoken interfaces is highly desirable, but problematic due to inherent limitations of speech. A speech widget for lists of attributed objects is described that provides for approximate queries to retrieve desired items. User tests demonstrate that this is an effective technique for accessing information using speech.
