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HCI research has for long been dedicated to better and more naturally facilitating information transfer between humans and machines. Unfortunately, humans' most natural form of communication, speech, is also one of the most difficult modalities to be understood by machines -- despite, and perhaps, because it is the highest-bandwidth communication channel we possess. While significant research efforts, from engineering, to linguistic, and to cognitive sciences, have been spent on improving machines' ability to understand speech, the CHI community has been relatively timid in embracing this modality as a central focus of research. This can be attributed in part to the relatively discouraging levels of accuracy in understanding speech, in contrast with often-unfounded claims of success from industry, but also to the intrinsic difficulty of designing and especially evaluating speech and natural language interfaces. As such, the development of interactive speech-based systems is mostly driven by engineering efforts to improve such systems with respect to largely arbitrary performance metrics, often void of any user-centered design principles or consideration for usability or usefulness.
Munteanu et al. (Sat,) studied this question.