We compare three tools for creating GOMS models, QGOMS [2), CATHCI (17) and GLEAN3 [12], along several dimensions. We examine the representation and available constructs in each tool, the qualitative and quantitative design information provided, the support for building cognitively plausible models, and pragmatics about using each tool (e.g., how easy it is to modify a model). While each tool has its strengths, they all leave something to be desired as a practical UI design tool.

The CMU Lexical Access system hypothesizes words from a phonetic lattice, supplemented by a coarse labelling of the speech signal. Word hypotheses are anchored on syllabic nuclei and are generated independently for different parts of the utterance. Junctures between words are resolved separately, on demand from the Parser module. The lexical representation is generated by rule from baseforms, in a completely automatic process. A description of the various components of the system is provided, as well as performance data.