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Vouch: multimodal touch-and-voice input for smart watches under difficult operating conditions

机译:凭证:在困难的操作条件下,用于智能手表的多模式触摸和语音输入

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摘要

We consider a multimodal method for smart-watch text entry, called "Vouch," which combines touch and voice input. Touch input is familiar and has good ergonomic accessibility, but is limited by the fat-finger problem (or equivalently, the screen size) and is sensitive to user motion. Voice input is mostly immune to slow user motion, but its reliability may suffer from environmental noise. Together, however, such characteristics can complement each other when coping with the difficult smart-watch operating conditions. With Vouch, the user makes an approximate touch among the densely distributed alphabetic keys; the accompanying voice input can be used to effectively disambiguate the target from among possible candidates, if not identify the target outright. We present a prototype implementation of the proposed multimodal input method and compare its performance and usability to the conventional unimodal method. We focus particularly on the potential improvement under difficult operating conditions, such as when the user is in motion. The comparative experiment validates our hypothesis that the Vouch multimodal approach would show more reliable recognition performance and higher usability.
机译:我们考虑了一种用于智能手表文本输入的多模式方法,称为“ Vouch”,该方法结合了触摸和语音输入。触摸输入是熟悉的并且具有良好的人体工程学可访问性,但是受到胖手指问题(或等效地,屏幕大小)的限制,并且对用户动作敏感。语音输入大部分不受用户缓慢移动的影响,但其可靠性可能会受到环境噪声的影响。但是,这些特征共同应对困难的智能手表操作条件时可以相互补充。使用Vouch,用户可以在密集分布的字母键之间进行大致触摸;如果未完全识别目标,则伴随的语音输入可用于有效地从可能的候选对象中消除目标的歧义。我们介绍了所提出的多模式输入法的原型实现,并将其性能和可用性与常规单模式方法进行了比较。我们特别关注在困难的操作条件下(例如用户运动时)的潜在改进。对比实验验证了我们的假设,即Vouch多峰方法将显示出更可靠的识别性能和更高的可用性。

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