Predicting and Managing Spoken Disfluencies During Human-Computer Interaction

PREDICTING AND MANAGING SPOKEN DISFLUENCIES DURING HUMAN-COMPUTER INTERACTION* Sharon Oviatt Computer Dialogue Laboratory & Artificial Intelligence Center SKI International, 333 Ravenswood Avenue, Menlo Park, CA. 94025 ABSTRACT 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 stud- ies involved within-subject factorial designs in which input modality and presentation format were varied. Spoken dis- fluency rates during human-computer interaction were doc- umented to be substantially lower than rates typically ob- served during comparable human-human speech. Two sep- arate factors, both associated with increased planning de- mands, were statistically related to increased speech disflu- ency rates: (1) length of utterance, and (2) lack of struc- ture in the presentation format. Regression techniques re- vealed 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 elimluated 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. 1. INTRODUCTION Recently, researchers interested in spoken language process- ing have begun searching for reliable methods to detect and correct disfluent input automatically during interactions with spoken language systems [2, 4, 9]. In general, this research has focused on identifying acoustic-prosodic cues for detect- ing self-repairs, either alone or in combination with syntac- tic, semantic, and pattern matching information. To date, however, possible avenues for simply reducing or eliminating disfluencies through manipulation of basic interface features have not been explored. Another underdeveloped but central theme in disfluency re- search is the relation between spoken disfluencies and plan- ning demands. Although it is frequently claimed that dis- fluencies rise with increased planning demands of different kinds [3], the nature of this relation remains poorly under- stood. The major factors contributing to planning have yet *This research was supported by Grant No. IRI-9213472 from the National Science Foundation, contracts from USWest, AT&T/NCR, and ATR International to SRI International, and equipment donations from Apple Computer, Sun Microsystems, and Wacom Inc. to be identified and defined in any comprehensive manner, or linked to disfluencies and self-repairs. From the viewpoint of designing systems, information on the dynarnics of what produces disfluencies, and how to structure interfaces to min- imize them, could improve the robust performance of spoken language systems. A related research issue is the extent to which qualitatively different types of speech may differ in their disfluency rates. That is, does the rate of spoken disfluencies tend to be stable, or variable? If variable, do disfluency rates differ systemat- ically between human-human and human-computer speech? And are disfluency rates sufficiently variable that techniques for designing spoken language …

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