PREDICTING AND MANAGING SPOKEN DISFLUENCIES DURING HUMAN-COMPUTER INTERACTION

摘要

This research characterizes the spontaneous spoken disfluen-cies typical of human-computer interaction, and presents a predictive model accounting for their occurrence. Data were collected during three empirical studies in which people spoke or wrote to a highly interactive simulated system. The studies involved within-subject factorial designs in which input modality and presentation format were varied. Spoken dis-fluency rates during human-computer interaction were documented to be substantially lower than rates typically observed during comparable human-human speech. Two separate factors, both associated with increased planning demands, were statistically related to increased speech disflu-ency rates: (1) length of utterance, and (2) lack of structure in the presentation format. Regression techniques revealed that a linear model based simply on utterance length accounts for over 77% of the variability in spoken disflu-encies. Therefore, design techniques capable of channeling users' speech into briefer sentences potentially could elim- inate most spoken disfluencies. In addition, the degree of structure in the presentation format was manipulated in a manner that successfully eliminated 60 to 70% of all disflu-ent speech. The long-term goal of this research is to provide empirical guidance for the design of robust spoken language technology.