Text and context in mobile computing

提出了一个研究计划，将重点放在“移动计算中的文本和上下文”上。我们所说的“文本”，只是指文本输入的问题。全球每天发送超过10亿条短信，手机键盘现在是占主导地位的文本输入设备之一-尽管它的文本输入能力很差。因此，研究手机文本输入是非常有价值的。在“语境”中，我们指的是通过对语言、用户或设备的内嵌知识来帮助文本输入的许多可能的机制。单词预测、单词补全、后缀补全是一些例子，但是与歧义键盘(例如，移动电话键盘每个键具有3个或4个字母)接口的一般问题特别令人感兴趣。随着移动设备尺寸的缩小，支持文本输入的兴趣越来越大，只需比手机包含的键更少的键。这是一个有趣的问题组合，将歧义解决问题与嵌入式语言模型混合在一起。为了解决歧义问题而增加击键次数(随着按键数量的减少)和使用预测性助手减少击键次数之间存在着矛盾。这是研究的肥沃土壤，也是提出的研究方案的主要重点。PI还广泛地与计算机定点设备、交互模型(例如，使用菲茨定律)以及对人类表现的测量一起工作。这些主题也是拟议的研究计划的一部分。

A program of research is proposed that will focus on "text and context in mobile computing". By "text", we refer simply to the issue of text entry. With over 1 billion SMS messages sent per day worldwide, the mobile phone keypad is now one of the dominant devices for text entry - this despite its poor capabilities for such. And so, a program of research in mobile text entry is extremely worthwhile. By "context", we refer to the many possible mechanisms to aide text entry through embedded knowledge of the language, user, or device. Word prediction, word completion, suffix completion, are some examples, but the general problem of interfacing with ambiguous keyboards (e.g., the mobile phone keyboard has either 3 or 4 letters per key) is of particular interest. As mobile devices shrink in size, there is increasing interest in supporting text entry with fewer keys than even a mobile phone contains. This presents an interesting combination of problems, intermixing issues of ambiguity resolution with an embedded language model. There is a tension between increasing keystrokes for ambiguity resolution (as the number of keys decreases) and decreasing keystrokes using predictive aides. This is fertile ground for research and it is the primary focus of the program of research proposed. The PI also works extensively with computer pointing devices, models of interaction (e.g., using Fitts' law), and the measurement of human performance. These topics are also part of the proposed program of research.