Design critiquing systems are a type of intelligent user interface used to support human designers in decision making. This paper places design critics in the larger context of intelligent user interface approaches and surveys several critiquing systems. Each approach and system is evaluated with respect to a five-phase design improvement process. This paper concludes with a summary of the state of the art in critiquing systems and recommendations for future research directions. 1.

This paper accounts for a new technique of correcting isolated words in typed texts. A language-dependent set of string substitutions reflects the surface form of errors that result from vocabulary incompetence, misspellings, or mistypings. Candidate corrections are formed by applying the substitutions to text words absent from the computer lexicon. A minimal acyclic deterministic finite automaton storing the lexicon allows quick rejection of nonsense corrections, while costs associated with the substitutions serve to rank the remaining ones. A comparison of the correction lists generated by several spellcheckers for two corpora of English spelling errors shows that our technique suggests the right words more accurately than the others.

Researchers have developed many models to predict and understand human performance in text entry. Most of the models are specific to a technology or fail to account for human factors and variations in system parameters, and the relationship between them. Moreover, the process of fixing errors and its effects on text entry performance has not been studied. Here, we first analyze real-life text entry error correction behaviors. We then use our findings to develop a new model to predict the cost of error correction for character-based text entry technologies. We validate our model against quantities derived from the literature, as well as with a user study. Our study shows that the predicted and observed costs of error correction correspond well. At the end, we discuss potential applications of our new model. Author Keywords User and cognitive model, performance metric, text entry, mobile phone, error correction.

NEC Foundation of America, NISH, Synaptics, and A.T. Sciences.

Recent improvements in text entry error rate measurement have enabled the running of text entry experiments in which subjects are free to correct errors (or not) as they transcribe a presented string. In these “unconstrained ” experiments, it is no longer necessary to force subjects to unnaturally maintain synchronicity with presented text for the sake of performing overall error rate calculations. However, the calculation of character-level error rates, which can be trivial in artificially constrained evaluations, is far more complicated in unconstrained text entry evaluations because it is difficult to infer a subject’s intention at every character. For this reason, prior characterlevel error analyses for unconstrained experiments have only compared presented and transcribed strings, not input streams. But input streams are rich sources of character-level error information, since they contain all of the text entered (and erased) by a subject. The current work presents an algorithm for the automated analysis of character-level errors in input streams for unconstrained text entry evaluations. It also presents new character-level metrics that can aid method designers in refining text entry methods. To exercise these metrics, we perform two analyses on data from an actual text entry experiment. One analysis, available from the prior work, uses only presented and transcribed strings. The other analysis uses input streams, as described in the current work. The results confirm that input stream error analysis yields richer information for the same empirical data. To facilitate the use of these new analyses, we offer pseudocode and downloadable software for performing unconstrained text entry experiments and analyzing data.

This thesis describes two experiments in nding errors in optically scanned Swedish without relying on a lexicon. First, statistics were used to nd unexpectedly frequent trigrams and correction rules for these cases were created. The rules were then tested and compared to a hand corrected version of the test text. Secondly, Bengt Sigurd's model of Swedish phonotax was used to detect words with phonotactically illegal beginning or end.

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