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Abstract
Voice interaction is a user-friendly interaction method for Mandarin Chinese. Voice perception has been widely implemented on smart devices for Mandarin voice interaction. However, previous studies gave little attention to how language features, such as the text type and text length affect the voice perception experience. Moreover, how the device type influences Mandarin voice perception is unclear, as the device type has been shown to have a significant effect on other interaction methods, such as interactions with keyboard entry and screen displays. Thus, the aim of this study was to investigate the effects of the text type, text length, and device type on the voice perception experience. This study invited seventy-two participants (36 females and 36 males) for an empirical experiment. Three text types, i.e., classical Chinese text, professional text, and daily text, three text lengths, namely, short (i.e., 10 characters), medium (i.e., 20 characters), and long (i.e., 30 characters), and two device types, i.e., mobile phones and smartwatches, were considered. Four measurements were used to evaluate the voice perception experience, namely, performance (i.e., self-reported performance and correct ratio), the satisfaction rating, mental workload, and skin conductance. The results indicate that the text type, text length, and device type had significant effects on the four measurements. Specifically, the voice perception experience was best for daily text and worst for classical Chinese text, shorter text led to a better voice perception experience, and users of smartwatches had a better voice perception experience than mobile phones. Furthermore, the design implications for improving the voice perception experience that consider the text type, text length, and device type were discussed.
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No potential conflict of interest was reported by the author(s).
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Notes on contributors
Zhe Chen
Zhe Chen is a lecturer in the School of Economics and Management, Beihang University. She received her PhD degree (human factor direction) at Tsinghua University.
Dongyue Liu
Dongyue Liu is a PhD candidate in the School of Economics and Management, Beihang University. He received his bachelor’s degree in industrial engineering in the School of Economics and Management, Beihang University.
Wenbo Zhu
Wenbo Zhu graduates from the Beihang University. He received his bachelor’s degree in industrial engineering in the School of Economics and Management, Beihang University.
Guozhu Jia
Guozhu Jia is a professor in the School of Economics and Management, Beihang University. He received his PhD degree at Aalborg University.
Ronggang Zhou
Ronggang Zhou is a professor in the School of Economics and Management, Beihang University. He received his PhD degree at Institute of Psychology, Chinese Academy of Sciences.