The vocabulary problem in human-system communication

TLDR

Computer applications require users to input correct words to access objects or actions. The study aims to enable systems to recognize spontaneously chosen terms for successful first‑attempt interactions without extensive training. The authors found that spontaneous word choice varies widely, with less than 20% agreement between users, leading to 80–90% failure rates for single‑word vocabularies, but an unlimited aliasing strategy can substantially improve success.

Abstract

In almost all computer applications, users must enter correct words for the desired objects or actions. For success without extensive training, or in first-tries for new targets, the system must recognize terms that will be chosen spontaneously. We studied spontaneous word choice for objects in five application-related domains, and found the variability to be surprisingly large. In every case two people favored the same term with probability <0.20. Simulations show how this fundamental property of language limits the success of various design methodologies for vocabulary-driven interaction. For example, the popular approach in which access is via one designer's favorite single word will result in 80-90 percent failure rates in many common situations. An optimal strategy, unlimited aliasing, is derived and shown to be capable of several-fold improvements.